MobileNetworkData.bib

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@Misc{All10a,
  file = {:All10a - Survey of Agent and Based Modelling and Simulation Tools. Technical Report DL TR.pdf:PDF},
}

@Book{FosGhaJarKreLan17a,
  Title                    = {Big Data and Social Science},
  Editor                   = {Ian Foster and Rayid Ghani and Ron S. Jarmin and Frauke Kreuter and Julia Lane},
  Publisher                = {{CRC} {P}ress},
  Year                     = {2017},

  Address                  = {Boca Raton},

  File                     = {:Foster et al - 2017 - Big data and social science_ a practical guide to methods and tools-Chapman.pdf:PDF},
  ISBN                     = {978-1-4987-5140-7}
}

@Book{LanStoBenNis14a,
  Title                    = {Privacy, Big Data, and the Public Good},
  Editor                   = {Julia Lane and Victoria Stodden and Stefan Bender and Helen Nissenbaum},
  Publisher                = {Cambridge University Press},
  Year                     = {2014},
  Note                     = {This is a preliminary version of the book},

  Doi                      = {10.1017/cbo9781107590205},
  File                     = {:Lane et al - 2014 - Privacy, Big Data, and the Public Good.pdf:PDF}
}

@Book{ZekBue12a,
  Title                    = {Handbook of Position Location: Theory, Practice, and Advances},
  Editor                   = {Seyed A. Zekavat and R. Michael Buehrer},
  Publisher                = {IEEE},
  Year                     = {2012},

  File                     = {:ZekBue - 2012 - Handbook of position location _ theory, practice and advances.pdf:PDF}
}

@Book{ZheZho11a,
  Title                    = {Computing with Spatial Trajectories},
  Editor                   = {Yu Zheng and Xiaofang Zhou},
  Publisher                = {Springer},
  Year                     = {2011},

  File                     = {:Zheng and Zhou -2011 - Computing with Spatial Trajectories.pdf:PDF}
}

@Book{AhsIly11a,
  Title                    = {Location-Based Services Handbook: Applications, Technologies, and Security},
  Editor                   = {S.A. Ahson and M. Ilyas},
  Publisher                = {{CRC} {P}ress},
  Year                     = {2011},

  File                     = {:Ahson and Ilyas - 2011 - Location-Based Services Handbook_ Applications, Technologies, and Security.pdf:PDF},
  ISBN                     = {978-1-4200-7198-6}
}

@Book{OHaWes10a,
  Title                    = {The Oxford Handbook of Applied Bayesian Analysis},
  Editor                   = {Anthony O\textquotesingle Hagan and Mike West},
  Publisher                = {Oxford University Press},
  Year                     = {2010},

  File                     = {:O'Hagan and West - 2010 - The Oxford Handbook of Applied Bayesian Analysis.pdf:PDF},
  Url                      = {978–0–19–954890–3}
}

@Book{PooWanRoy07a,
  Title                    = {Secure Localization and Time Synchronization for Wireless Sensor and Ad Hoc Networks},
  Editor                   = {Radha Poovendran and Cliff Wang and Sumit Roy},
  Publisher                = {Springer},
  Year                     = {2007},

  File                     = {:Poovendran et al - 2007 - Secure Localization and Time Synchronization for Wireless Sensor and Ad Hoc Networks.pdf:PDF}
}

@Book{KinRosTan04a,
  title     = {Ecological Inference: New Methodological Strategies},
  publisher = {Cambridge University Press},
  year      = {2004},
  editor    = {Gary King and Ori Rosen and Martin A. Tanner},
  file      = {:KinRosTan04a - Ecological Inference_ New Methodological Strategies.pdf:PDF},
}

@Book{GelMen04a,
  Title                    = {Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives},
  Editor                   = {Andrew Gelman and Xiao-Li Meng},
  Publisher                = {John Wiley \& Sons},
  Year                     = {2004},

  File                     = {:Gelman and Meng - 2004 - Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives.pdf:PDF}
}

@Book{HalRomMel03a,
  Title                    = {{GSM}, {GPRS} and {EDGE} Performance},
  Editor                   = {Timo Halonen and Javier Romero and Juan Melero},
  Publisher                = {John Wiley {\&} Sons, Ltd},
  Year                     = {2003},
  Month                    = sep,

  Doi                      = {10.1002/0470866969},
  File                     = {:Halonen et al - 2003 - GSM, GPRS and EDGE Performance_ Evolution Towards 3G_UMTS - 2nd ed.pdf:PDF}
}

@Article{ZorLey18a,
  author    = {Hamidreza Zoraghein and Stefan Leyk},
  title     = {Enhancing areal interpolation frameworks through dasymetric refinement to create consistent population estimates across censuses},
  journal   = {International Journal of Geographical Information Science},
  year      = {2018},
  volume    = {32},
  number    = {10},
  pages     = {1948--1976},
  month     = may,
  doi       = {10.1080/13658816.2018.1472267},
  publisher = {Informa {UK} Limited},
}

@Article{ZilNag15a,
  author    = {Michael Zilske and Kai Nagel},
  title     = {A Simulation-based Approach for Constructing All-day Travel Chains from Mobile Phone Data},
  journal   = {Procedia Computer Science},
  year      = {2015},
  volume    = {52},
  pages     = {468--475},
  doi       = {10.1016/j.procs.2015.05.017},
  publisher = {Elsevier {BV}},
}

@Article{ZilNag14a,
  author    = {Michael Zilske and Kai Nagel},
  title     = {Studying the Accuracy of Demand Generation from Mobile Phone Trajectories with Synthetic Data},
  journal   = {Procedia Computer Science},
  year      = {2014},
  volume    = {32},
  pages     = {802--807},
  doi       = {10.1016/j.procs.2014.05.494},
  keywords  = {transport simulation; multi-agent simulation; mobile phone data},
  publisher = {Elsevier {BV}},
}

@InProceedings{ZilsNag13a,
  author    = {Michael Zilske and Kai Nagel},
  title     = {Building a minimal traffic model from mobile phone data},
  booktitle = {Proceedings of the third international conference NetMob D4D Challenge},
  year      = {2013},
  address   = {Boston, MA, USA},
  month     = may,
}

@Article{ZhuCre14a,
  author    = {Lili Zhuang and Noel Cressie},
  title     = {Bayesian hierarchical statistical {SIRS} models},
  journal   = {Statistical Methods {\&} Applications},
  year      = {2014},
  volume    = {23},
  number    = {4},
  pages     = {601--646},
  month     = nov,
  doi       = {10.1007/s10260-014-0280-9},
  publisher = {Springer Nature},
}

@Article{ZhaYiYanMinWanElmMahZha16a,
  author    = {Xing Zhang and Zhenglei Yi and Zhi Yan and Geyong Min and Wenbo Wang and Ahmed Elmokashfi and Sabita Maharjan and Yan Zhang},
  title     = {Social Computing for Mobile Big Data},
  journal   = {Computer},
  year      = {2016},
  volume    = {49},
  number    = {9},
  pages     = {86--90},
  month     = sep,
  doi       = {10.1109/mc.2016.267},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Zha11a,
  author    = {Li-Chun Zhang},
  title     = {Topics of statistical theory for register-based statistics and data integration},
  journal   = {Statistica Neerlandica},
  year      = {2011},
  volume    = {66},
  number    = {1},
  pages     = {41--63},
  month     = nov,
  doi       = {10.1111/j.1467-9574.2011.00508.x},
  publisher = {Wiley},
}

@InProceedings{Zer18a,
  author    = {Federico Zerba},
  title     = {Big data tools and tourism market intelligence},
  booktitle = {15\textsuperscript{th} Global Forum on Tourism Statistics},
  year      = {2018},
  keywords  = {Big Data, Tourism Intelligence System, Competitiveness, Information},
}

@Article{ZeiKleJac08a,
  author    = {Achim Zeileis and Christian Kleiber and Simon Jackman},
  title     = {Regression Models for Count Data {inR}},
  journal   = {Journal of Statistical Software},
  year      = {2008},
  volume    = {27},
  number    = {8},
  doi       = {10.18637/jss.v027.i08},
  keywords  = {GLM, Poisson model, negative binomial model, hurdle model, zero-inflated model},
  publisher = {Foundation for Open Access Statistic},
}

@TechReport{Zee16a,
  Title                    = {Big Data and Methodological Challenges in Official Statistics},
  Author                   = {Kees Zeelenberg},
  Institution              = {Statistics Netherlands},
  Year                     = {2016},

  File                     = {:Zee16a - Kees Zeelenberg.pdf:PDF}
}

@Article{ZahSha16a,
  author    = {Seyedmostafa Zahedi and Yousef Shafahi},
  title     = {Estimating Activity Patterns Using Spatio-temporal Data of Cellphone Networks},
  journal   = {{MATEC} Web of Conferences},
  year      = {2016},
  volume    = {81},
  pages     = {04011},
  doi       = {10.1051/matecconf/20168104011},
  editor    = {M. Figueira and Z. Guo},
  publisher = {{EDP} Sciences},
}

@Article{YuaRau16a,
  author    = {Yihong Yuan and Martin Raubal},
  title     = {Exploring Georeferenced Mobile Phone Datasets - A Survey and Reference Framework},
  journal   = {Geography Compass},
  year      = {2016},
  volume    = {10},
  number    = {6},
  pages     = {239--252},
  month     = jun,
  doi       = {10.1111/gec3.12269},
  publisher = {Wiley},
}

@InCollection{YinYeLeeLi14a,
  author    = {Peifeng Yin and Mao Ye and Wang-Chien Lee and Zhenhui Li},
  title     = {Mining {GPS} Data for Trajectory Recommendation},
  booktitle = {Advances in Knowledge Discovery and Data Mining},
  publisher = {Springer International Publishing},
  year      = {2014},
  pages     = {50--61},
  abstract  = {The wide use of GPS sensors in smart phones encourages
people to record their personal trajectories and share them with others
in the Internet. A recommendation service is needed to help people pro-
cess the large quantity of trajectories and select potentially interesting
ones. The GPS trace data is a new format of information and few works
focus on building user preference profiles on it. In this work we proposed
a trajectory recommendation framework and developed three recommen-
dation methods, namely, Activity-Based Recommendation (ABR), GPS-
Based Recommendation (GBR) and Hybrid Recommendation. The ABR
recommends trajectories purely relying on activity tags. For GBR, we
proposed a generative model to construct user profiles based on GPS
traces. The Hybrid recommendation combines the ABR and GBR. We
finally conducted extensive experiments to evaluate these proposed solu-
tions and it turned out the hybrid solution displays the best performance.},
  doi       = {10.1007/978-3-319-06605-9_5},
}

@Article{YinSheFeyPaiPoz18a,
  author    = {Mogeng Yin and Madeleine Sheehan and Sidney Feygin and Jean-Francois Paiement and Alexei Pozdnoukhov},
  title     = {A Generative Model of Urban Activities from Cellular Data},
  journal   = {{IEEE} Transactions on Intelligent Transportation Systems},
  year      = {2018},
  volume    = {19},
  number    = {6},
  pages     = {1682--1696},
  month     = jun,
  doi       = {10.1109/tits.2017.2695438},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Book{YinZha05a,
  Title                    = {Discrete-Time Markov Chains},
  Author                   = {G. George Yin and Qing Zhang},
  Publisher                = {Springer},
  Year                     = {2005},

  File                     = {:Yin and Zhang - 2005 - Discrete-time Markov Chains_ Two-time-scale Methods and Applications.pdf:PDF}
}

@Misc{YanBer12a,
  Title                    = {A Catalog of Noninformative Priors},

  Author                   = {Ruoyong Yang and James O. Berger},

  File                     = {:YanBer12a - Ruoyong Yang and James O. Berger.pdf:PDF}
}

@Article{YanNguBla14a,
  author    = {Chun Yang and Thao Nguyen and Erik Blasch},
  title     = {Mobile positioning via fusion of mixed signals of opportunity},
  journal   = {{IEEE} Aerospace and Electronic Systems Magazine},
  year      = {2014},
  volume    = {29},
  number    = {4},
  pages     = {34--46},
  month     = apr,
  doi       = {10.1109/maes.2013.130105},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{XuShaZhaYinFanLi15a,
  author    = {Yang Xu and Shih-Lung Shaw and Ziliang Zhao and Ling Yin and Zhixiang Fang and Qingquan Li},
  title     = {Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach},
  journal   = {Transportation},
  year      = {2015},
  volume    = {42},
  number    = {4},
  pages     = {625--646},
  month     = mar,
  doi       = {10.1007/s11116-015-9597-y},
  file      = {:XuShaZhaYinFanLi15a - Understanding Aggregate Human Mobility Patterns Using Passive Mobile Phone Location Data_ a Home Based Approach.pdf:PDF},
  publisher = {Springer Nature},
}

@Article{XuBelBojRat17a,
  author    = {Yang Xu and Alexander Belyi and Iva Bojic and Carlo Ratti},
  title     = {How friends share urban space: An exploratory spatiotemporal analysis using mobile phone data},
  journal   = {Transactions in {GIS}},
  year      = {2017},
  volume    = {21},
  number    = {3},
  pages     = {468--487},
  month     = jun,
  doi       = {10.1111/tgis.12285},
  publisher = {Wiley},
}

@PhdThesis{Xu13a,
  Title                    = {Improving the Spatial Accuracy of Mobile Positioning Data Based on Fine-Scale Human Mobility Pattern Analysis},
  Author                   = {Li Xu},
  School                   = {University of Colorado, Boulder},
  Year                     = {2013},

  File                     = {:Xu13a - Li Xu.pdf:PDF}
}

@Article{XuGaoDanWanLiu17a,
  author    = {Guangxia Xu and Shiyi Gao and Mahmoud Daneshmand and Chonggang Wang and Yanbing Liu},
  title     = {A Survey for Mobility Big Data Analytics for Geolocation Prediction},
  journal   = {{IEEE} Wireless Communications},
  year      = {2017},
  volume    = {24},
  number    = {1},
  pages     = {111--119},
  month     = feb,
  doi       = {10.1109/mwc.2016.1500131wc},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{XiaWanKonWanLiLiu18a,
  author    = {Feng Xia and Jinzhong Wang and Xiangjie Kong and Zhibo Wang and Jianxin Li and Chengfei Liu},
  title     = {Exploring Human Mobility Patterns in Urban Scenarios: A Trajectory Data Perspective},
  journal   = {{IEEE} Communications Magazine},
  year      = {2018},
  volume    = {56},
  number    = {3},
  pages     = {142--149},
  month     = mar,
  doi       = {10.1109/mcom.2018.1700242},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{WuXuZenZheQuNiYuaNi16,
  author    = {Wenchao Wu and Jiayi Xu and Haipeng Zeng and Yixian Zheng and Huamin Qu and Bing Ni and Mingxuan Yuan and Lionel M. Ni},
  title     = {{TelCoVis}: Visual Exploration of Co-occurrence in Urban Human Mobility Based on Telco Data},
  journal   = {{IEEE} Transactions on Visualization and Computer Graphics},
  year      = {2016},
  volume    = {22},
  number    = {1},
  pages     = {935--944},
  month     = jan,
  doi       = {10.1109/tvcg.2015.2467194},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{WuYanXuZhaLiu15a,
  author    = {Chenshu Wu and Zheng Yang and Yu Xu and Yiyang Zhao and Yunhao Liu},
  title     = {Human Mobility Enhances Global Positioning Accuracy for Mobile Phone Localization},
  journal   = {{IEEE} Transactions on Parallel and Distributed Systems},
  year      = {2015},
  volume    = {26},
  number    = {1},
  pages     = {131--141},
  month     = jan,
  doi       = {10.1109/tpds.2014.2308225},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{WitMeiLeiSheGusTufHanDarMolConWin16a,
  author    = {Klaus Witrisal and Paul Meissner and Erik Leitinger and Yuan Shen and Carl Gustafson and Fredrik Tufvesson and Katsuyuki Haneda and Davide Dardari and Andreas F. Molisch and Andrea Conti and Moe Z. Win},
  title     = {High-Accuracy Localization for Assisted Living: 5G systems will turn multipath channels from foe to friend},
  journal   = {{IEEE} Signal Processing Magazine},
  year      = {2016},
  volume    = {33},
  number    = {2},
  pages     = {59--70},
  month     = mar,
  doi       = {10.1109/msp.2015.2504328},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{WitHeuRom12a,
  author    = {Ernst Wit and Edwin van den Heuvel and Jan-Willem Romeijn},
  title     = {`All models are wrong...': an introduction to model uncertainty},
  journal   = {Statistica Neerlandica},
  year      = {2012},
  volume    = {66},
  number    = {3},
  pages     = {217--236},
  month     = jul,
  doi       = {10.1111/j.1467-9574.2012.00530.x},
  publisher = {Wiley},
}

@Article{WisSmiBijRayFor15a,
  author    = {Arkadiusz Wi{\'{s}}niowski and Peter W. F. Smith and Jakub Bijak and James Raymer and Jonathan J. Forster},
  title     = {Bayesian Population Forecasting: Extending the Lee-Carter Method},
  journal   = {Demography},
  year      = {2015},
  volume    = {52},
  number    = {3},
  pages     = {1035--1059},
  month     = may,
  doi       = {10.1007/s13524-015-0389-y},
  publisher = {Springer Nature},
}

@TechReport{Wil16a,
  Title                    = {Statistical uses for mobile phone data: literature review},
  Author                   = {Susan Williams},
  Institution              = {Office for National Statistics},
  Year                     = {2016},

  File                     = {:Wil16a - Susan Williams.pdf:PDF}
}

@Article{WilPfaRegPar15a,
  author    = {Chris J. Wild and Maxine Pfannkuch and Matt Regan and Ross Parsonage},
  title     = {Accessible Conceptions of Statistical Inference: Pulling Ourselves Up by the Bootstraps},
  journal   = {International Statistical Review},
  year      = {2015},
  volume    = {85},
  number    = {1},
  pages     = {84--107},
  month     = sep,
  doi       = {10.1111/insr.12117},
  publisher = {Wiley},
}

@Article{WheRafClaGer15a,
  author    = {Mark C. Wheldon and Adrian E. Raftery and Samuel J. Clark and Patrick Gerland},
  title     = {Bayesian reconstruction of two-sex populations by age: estimating sex ratios at birth and sex ratios of mortality},
  journal   = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  year      = {2015},
  volume    = {178},
  number    = {4},
  pages     = {977--1007},
  month     = feb,
  doi       = {10.1111/rssa.12104},
  keywords  = {Bayesian hierarchical model; Population projection; Sex ratio at birth; Sex ratio of mortality; Two-sex model; Vital rates},
  publisher = {Wiley},
}

@Article{WesMetEagKomGrenBjoLesTatBuc15a,
  author    = {Amy Wesolowski and C. J. E. Metcalf and Nathan Eagle and Janeth Kombich and Bryan T. Grenfell and Ottar N. Bj{\o}rnstad and Justin Lessler and Andrew J. Tatem and Caroline O. Buckee},
  title     = {Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {2015},
  volume    = {112},
  number    = {35},
  pages     = {11114--11119},
  month     = aug,
  doi       = {10.1073/pnas.1423542112},
  publisher = {Proceedings of the National Academy of Sciences},
}

@Article{WesEagNooSnoBuc13a,
  author    = {A. Wesolowski and N. Eagle and A. M. Noor and R. W. Snow and C. O. Buckee},
  title     = {The impact of biases in mobile phone ownership on estimates of human mobility},
  journal   = {Journal of The Royal Society Interface},
  year      = {2013},
  volume    = {10},
  number    = {81},
  pages     = {20120986--20120986},
  month     = feb,
  doi       = {10.1098/rsif.2012.0986},
  publisher = {The Royal Society},
}

@Article{WesBucPinEagSmiGarTat13a,
  author    = {Amy Wesolowski and Caroline O. Buckee and Deepa K. Pindolia and Nathan Eagle and David L. Smith and Andres J. Garcia and Andrew J. Tatem},
  title     = {The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales},
  journal   = {{PLoS} {ONE}},
  year      = {2013},
  volume    = {8},
  number    = {1},
  pages     = {e52971},
  month     = jan,
  doi       = {10.1371/journal.pone.0052971},
  editor    = {John P. Hart},
  publisher = {Public Library of Science ({PLoS})},
}

@InCollection{Wer14a,
  author    = {Martin Werner},
  title     = {Basic Positioning Techniques},
  booktitle = {Indoor Location-Based Services},
  publisher = {Springer International Publishing},
  year      = {2014},
  pages     = {73--99},
  doi       = {10.1007/978-3-319-10699-1_3},
}

@Article{WanHeLeu18a,
  author    = {Zhenzhen Wang and Sylvia Y. He and Yee Leung},
  title     = {Applying mobile phone data to travel behaviour research: A literature review},
  journal   = {Travel Behaviour and Society},
  year      = {2018},
  volume    = {11},
  pages     = {141--155},
  month     = apr,
  doi       = {10.1016/j.tbs.2017.02.005},
  file      = {:WanHeLeu18a - Applying Mobile Phone Data to Travel Behaviour Research_ a Literature Review.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@PhdThesis{Wan14a,
  Title                    = {Understanding Activity Location Choice with Mobile Phone Data},
  Author                   = {Menglin Wang},
  School                   = {University of Washington},
  Year                     = {2014},

  File                     = {:Wan14a - Menglin Wang.pdf:PDF}
}

@Article{WanHuaZhoHuaZho15a,
  Title                    = {Cognition-inspired route evaluation using mobile phone data},
  Author                   = {Hui Wang and Jiajin Huang and Erzhong Zhou and Zhisheng Huang and Ning Zhong},
  Journal                  = {Natural Computing},
  Year                     = {2015},

  Month                    = feb,
  Number                   = {4},
  Pages                    = {637--648},
  Volume                   = {14},

  Doi                      = {10.1007/s11047-014-9479-9},
  File                     = {:WanHuaZhoHuaZho15a - Hui Wang and Jiajin Huang and Erzhong Zhou and Zhisheng Huang and Ning Zhong.pdf:PDF},
  Publisher                = {Springer Nature}
}

@InProceedings{WanPedSonGiaBar11a,
  author    = {Dashun Wang and Dino Pedreschi and Chaoming Song and Fosca Giannotti and Albert-Laszlo Barabasi},
  title     = {Human mobility, social ties, and link prediction},
  booktitle = {Proceedings of the 17\textsuperscript{th} {ACM} {SIGKDD} international conference on Knowledge discovery and data mining - {KDD} {\textquotesingle}11},
  year      = {2011},
  publisher = {{ACM} Press},
  abstract  = {1. INTRODUCTION
Our understanding of how individual mobility patterns shape Social networks have attracted particular interest in recent},
  doi       = {10.1145/2020408.2020581},
  keywords  = {29] and its predictability [30]. Indeed, despite the inhomo- Human Mobility, Link Prediction, Social Network geneous spatial resolution (the uneven reception area of mo},
}

@InProceedings{WalPoz11a,
  Title                    = {Spatial structure and dynamics of urban communities},
  Author                   = {Fergal Walsh and Alexei Pozdnoukhov},
  Booktitle                = {First Workshop on Pervasive Urban Applications (PURBA) at Ninth International Conference on Pervasive Computing},
  Year                     = {2011},

  Address                  = {San Francisco, USA},
  Month                    = jun,

  Abstract                 = {This paper explores the evolution and spatial organization
of urban communities in a daily cycle of a city using scalable methods
of social network analysis. Using mobile phone network records, we have
observed spatial patterns in community structures at fine spatial scales
which are most likely related to the activities typical to the different
functional regions of a city. It is known that interactions between different
parts of the city are subject to a distance decay, moreover, our findings
show that regardless of the time of the day or current activity, people tend
to communicate within a spatially enclosed community. Furthermore, we
have investigated transitions and transformations of these communities
at the temporal scales of several hours related to the cycles of human
movement and activities in a city.},
  File                     = {:WalPoz11a - Fergal Walsh and Alexei Pozdnoukhov.pdf:PDF},
  Keywords                 = {community detection, complex networks, smart city, mobile phone data}
}

@TechReport{deWvDeSch17a,
  Title                    = {Framework for the quality evaluation of statistical output based on multiple sources},
  Author                   = {Ton de Waal and Arnout van Delden and Sander Scholtus},
  Institution              = {Statistics Netherlands},
  Year                     = {2017},
  Month                    = aug,
  Number                   = {2017},
  Type                     = {resreport},

  File                     = {:deWvDeSch17a - Ton de Waal and Arnout van Delden and Sander Scholtus.pdf:PDF},
  Url                      = {https://ec.europa.eu/eurostat/cros/content/wp3-framework-quality-evaluation-statistical-output-based-multiple-sources_en}
}

@TechReport{VizVil18a,
  Title                    = {Intelligent use of mobile positioning data to measure domestic tourism in Peru: the case of the {\textquoteleft}Vamos pal Norte{\textquotedblright} campaign},
  Author                   = {Walter Vizarreta and Leyge Villanueva},
  Institution              = {15\textsuperscript{th} World Forum on Tourism Statistics},
  Year                     = {2018},
  Number                   = {explore},

  File                     = {:VizVil18a - Walter Vizarreta and Leyge Villanuevaa.pdf:PDF},
  Url                      = {http://www.15th-tourism-stats-forum.com/results.html}
}

@Misc{VivSaa10a,
  Title                    = {Privacy in the era of big data and learning analytics: ethical considerations and positions},

  Author                   = {Marianna Vivitsou and Mohsen Saadatmand},
  HowPublished             = {ACM Conference},
  Year                     = {2010},

  Doi                      = {10.1145/12345.67890},
  File                     = {:VivSaa10a - Marianna Vivitsou and Mohsen Saadatmand.pdf:PDF}
}

@Article{VisTroMukNasBou16a,
  author    = {Alexander A. Visheratin and Tamara B. Trofimenko and Ksenia D. Mukhina and Denis Nasonov and Alexander V. Boukhanovsky},
  title     = {Urgent Information Spreading Multi-layer Model for Simulation in Mobile Networks},
  journal   = {Procedia Computer Science},
  year      = {2016},
  volume    = {80},
  pages     = {2086--2097},
  doi       = {10.1016/j.procs.2016.05.528},
  publisher = {Elsevier {BV}},
}

@Article{VirRosMorChaGir16a,
  author    = {Seppo Virtanen and Mattias Rost and Alistair Morrison and Matthew Chalmers and Mark Girolami},
  title     = {Uncovering smartphone usage patterns with multi-view mixed membership models},
  journal   = {Stat},
  year      = {2016},
  volume    = {5},
  number    = {1},
  pages     = {57--69},
  doi       = {10.1002/sta4.103},
  publisher = {Wiley},
}

@Article{VehOja12a,
  author    = {Aki Vehtari and Janne Ojanen},
  title     = {A survey of Bayesian predictive methods for model assessment, selection and comparison},
  journal   = {Statistics Surveys},
  year      = {2012},
  volume    = {6},
  number    = {0},
  pages     = {142--228},
  doi       = {10.1214/12-ss102},
  publisher = {Institute of Mathematical Statistics},
}

@Article{VazCam13a,
  author  = {Eric Vaz and Ana Claudia Campos},
  title   = {A Multi-Dasymetric Mapping Approach for Tourism},
  journal = {Journal of Spatial and Organizational Dynamics, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve},
  year    = {2013},
  volume  = {1},
  number  = {4},
  pages   = {265--277},
}

@Article{VanReiSmoPlo18a,
  author   = {Maarten Vanhoof and Fernando Reis and Zbigniew Smoreda and Thomas Pl\"{o}tz},
  title    = {Detecting Home Locations from CDR Data: Introducing Spatial Uncertainty to the State-of-the-Art},
  journal  = {arXiv:1808.06398 [cs.CY]},
  year     = {2018},
  note     = {Contribution to the Mobile Tartu 2016 Conference},
  abstract = {Non-continuous location traces inferred from Call Detail Records (CDR) at population scale are increasingly becoming available for research and show great potential for automated detection of meaningful places. Yet, a majority of Home Detection Algorithms (HDAs) suffer from {\textquotedblleft}blind{\textquotedblright} deployment of criteria to define homes and from limited possibilities for validation. In this paper, we investigate the performance and capabilities of five popular criteria for home detection based on a very large mobile phone dataset from France (~18 million users, 6 months). Furthermore, we construct a data-driven framework to assess the spatial uncertainty related to the application of HDAs. Our findings appropriate patial uncertainty in HDA and, in extension, for detection of meaningful places. We show how spatial uncertainties on the individuals{\textquoteright} level can be assessed in absence of ground truth annotation, how they relate to traditional, igh-level validation practices and how they can be used to improve results for, e.g., nation-wide population estimation.},
}

@Article{VanPloSmo18a,
  author  = {Maarten Vanhoof and Thomas Pl\"{o}tz and Zbigniew Smoreda},
  title   = {Geographical veracity of indicators derived from mobile phone data},
  journal = {arXiv:1809.09912 [cs.CY]},
  year    = {2018},
}

@Article{Val15a,
  author    = {Steven Vale},
  title     = {International collaboration to understand the relevance of Big Data for official statistics},
  journal   = {Statistical Journal of the IAOS},
  year      = {2015},
  volume    = {31},
  number    = {2},
  pages     = {159--163},
  month     = may,
  issn      = {1874-7655},
  doi       = {10.3233/sji-150889},
  publisher = {IOS Press},
}

@Article{VajVajLil15a,
  author    = {Toivo Vajakas and Jaan Vajakas and Rauni Lillemets},
  title     = {Trajectory reconstruction from mobile positioning data using cell-to-cell travel time information},
  journal   = {International Journal of Geographical Information Science},
  year      = {2015},
  volume    = {29},
  number    = {11},
  pages     = {1941--1954},
  month     = may,
  doi       = {10.1080/13658816.2015.1049540},
  publisher = {Informa {UK} Limited},
}

@Article{UttJoh08a,
  author    = {Jessica Utts and Wesley Johnson},
  title     = {The Evolution of Teaching Bayesian Statistics to Nonstatisticians},
  journal   = {The American Statistician},
  year      = {2008},
  volume    = {62},
  number    = {3},
  pages     = {199--201},
  month     = aug,
  doi       = {10.1198/000313008x330810},
  publisher = {Informa {UK} Limited},
}

@TechReport{ITU17a,
  Title                    = {Call Detail Record (CDR). Analysis: Republic of Guinea},
  Author                   = {International Telecommunication Union},
  Institution              = {International Telecommunication and Union},
  Year                     = {2017},

  File                     = {:ITU17a - International Telecommunication Union.pdf:PDF}
}

@InProceedings{UNDESAUNECE15a,
  Title                    = {Results of the UNSD/UNECE Survey on organizational context and individual projects of Big Data},
  Author                   = {Statistics Divisions of UN/DESA and UN Economic Commission for Europe},
  Booktitle                = {Statistical Commission Forty-sixth session},
  Year                     = {2015},

  File                     = {:UNDESAUNECE15a - Statistics Divisions of UN_DESA and UN Economic Commission for Europe.pdf:PDF}
}

@TechReport{UaESMC12a,
  Title                    = {Review of the state of the art in secure multiparty computation},
  Author                   = {UaESMC},
  Institution              = {Project 'Usable and Efficient Secure Multiparty Computation'},
  Year                     = {2012},
  Month                    = may,

  File                     = {:UaESMC12a - UaESMC.pdf:PDF}
}

@Article{TwoCad02a,
  author    = {Paul Twomey and Richard Cadman},
  title     = {Agent-based modelling of customer behaviour in the telecoms and media markets},
  journal   = {info},
  year      = {2002},
  volume    = {4},
  number    = {1},
  pages     = {56--63},
  month     = feb,
  abstract  = {Agent-based modelling is a bottom-up approach to for those markets characterized by non-linearity and},
  doi       = {10.1108/14636690210426640},
  keywords  = {Modelling, Consumer behaviour, United Kingdom, techniques continue to be powerful tools, in certain markets Telecommunications, Broadcasting their appropriateness can be called into question, especially},
  publisher = {Emerald},
}

@Article{TuyGerMen08a,
  author    = {Frank Tuyl and Richard Gerlach and Kerrie Mengersen},
  title     = {A Comparison of Bayes{\textendash}Laplace, Jeffreys, and Other Priors},
  journal   = {The American Statistician},
  year      = {2008},
  volume    = {62},
  number    = {1},
  pages     = {40--44},
  month     = feb,
  doi       = {10.1198/000313008x267839},
  publisher = {Informa {UK} Limited},
}

@Article{TsaLaiChaVas15a,
  author    = {Chun-Wei Tsai and Chin-Feng Lai and Han-Chieh Chao and Athanasios V. Vasilakos},
  title     = {Big data analytics: a survey},
  journal   = {Journal of Big Data},
  year      = {2015},
  volume    = {2},
  number    = {1},
  month     = oct,
  doi       = {10.1186/s40537-015-0030-3},
  publisher = {Springer Nature},
}

@Article{TraOltRaiNanCouFurGiaSmoZie15a,
  author    = {Roberto Trasarti and Ana-Maria Olteanu-Raimond and Mirco Nanni and Thomas Couronn{\'{e}} and Barbara Furletti and Fosca Giannotti and Zbigniew Smoreda and Cezary Ziemlicki},
  title     = {Discovering urban and country dynamics from mobile phone data with spatial correlation patterns},
  journal   = {Telecommunications Policy},
  year      = {2015},
  volume    = {39},
  number    = {3-4},
  pages     = {347--362},
  month     = may,
  doi       = {10.1016/j.telpol.2013.12.002},
  publisher = {Elsevier {BV}},
}

@Article{TraNij15a,
  author    = {Emmanouil Tranos and Peter Nijkamp},
  title     = {Mobile phone usage in complex urban systems: a space{\textendash}time, aggregated human activity study},
  journal   = {Journal of Geographical Systems},
  year      = {2015},
  volume    = {17},
  number    = {2},
  pages     = {157--185},
  month     = mar,
  doi       = {10.1007/s10109-015-0211-9},
  publisher = {Springer Nature},
}

@InProceedings{TraBroCalMor11a,
  Title                    = {Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Inference},
  Author                   = {V.A. Traag and A. Browet and F. Calabrese and F. Morlot},
  Booktitle                = {2011 {IEEE} Third Int{\textquotesingle}l Conference on Privacy, Security, Risk and Trust and 2011 {IEEE} Third Int{\textquotesingle}l Conference on Social Computing},
  Year                     = {2011},
  Month                    = oct,
  Publisher                = {{IEEE}},

  Doi                      = {10.1109/passat/socialcom.2011.133},
  File                     = {:TraBroCalMor11a - V.A. Traag and A. Browet and F. Calabrese and F. Morlot.pdf:PDF}
}

@Article{Tor10a,
  author    = {Paul M. Torrens},
  title     = {Agent-based Models and the Spatial Sciences},
  journal   = {Geography Compass},
  year      = {2010},
  volume    = {4},
  number    = {5},
  pages     = {428--448},
  month     = may,
  doi       = {10.1111/j.1749-8198.2009.00311.x},
  publisher = {Wiley},
}

@InProceedings{TooUlmGonBau12a,
  Title                    = {Inferring land use from mobile phone activity},
  Author                   = {Jameson L. Toole and Michael Ulm and Marta C. Gonz{\'{a}}lez and Dietmar Bauer},
  Booktitle                = {Proceedings of the {ACM} {SIGKDD} International Workshop on Urban Computing - {UrbComp} {\textquotesingle}12},
  Year                     = {2012},
  Publisher                = {{ACM} Press},

  Abstract                 = {General Terms
Understanding the spatiotemporal distribution of people within Design, Measurement, Human Factors
a city is crucial to many planning applications. Obtaining
data to create required knowledge, currently involves costly
survey methods. At the same time ubiquitous mobile sen- Keywords
sors from personal GPS devices to mobile phones are col- Urban Computing, Human Mobility, Land Use, Dynamic},
  Doi                      = {10.1145/2346496.2346498},
  File                     = {:TooUlmGonBau12a - Jameson L. Toole and Michael Ulm and Marta C. Gonz{_'{a}}lez and Dietmar Bauer.pdf:PDF}
}

@Article{TooHerYaqSchGon15a,
  author    = {J. L. Toole and C. Herrera-Yaque and C. M. Schneider and M. C. Gonz\'{a}lez},
  title     = {Coupling human mobility and social ties},
  journal   = {Journal of The Royal Society Interface},
  year      = {2015},
  volume    = {12},
  number    = {105},
  pages     = {20141128--20141128},
  month     = feb,
  doi       = {10.1098/rsif.2014.1128},
  publisher = {The Royal Society},
}

@Article{TomBek18a,
  author    = {Slavisa Tomic and Marko Beko},
  title     = {A bisection-based approach for exact target localization in {NLOS} environments},
  journal   = {Signal Processing},
  year      = {2018},
  volume    = {143},
  pages     = {328--335},
  month     = feb,
  doi       = {10.1016/j.sigpro.2017.09.019},
  publisher = {Elsevier {BV}},
}

@Article{TolPsaPri17a,
  author    = {Reza Tolouei and Stefanos Psarras and Rawle Prince},
  title     = {Origin-Destination Trip Matrix Development: Conventional Methods versus Mobile Phone Data},
  journal   = {Transportation Research Procedia},
  year      = {2017},
  volume    = {26},
  pages     = {39--52},
  doi       = {10.1016/j.trpro.2017.07.007},
  publisher = {Elsevier {BV}},
}

@Article{TocLerBenZioBenGal18a,
  author    = {Eran Toch and Boaz Lerner and Eyal Ben-Zion and Irad Ben-Gal},
  title     = {Analyzing large-scale human mobility data: a survey of machine learning methods and applications},
  journal   = {Knowledge and Information Systems},
  year      = {2018},
  month     = mar,
  doi       = {10.1007/s10115-018-1186-x},
  publisher = {Springer Nature},
}

@Article{ThuiMoaLamCam18a,
  author    = {Etienne Thuillier and Laurent Moalic and Sid Lamrous and Alexandre Caminada},
  title     = {Clustering Weekly Patterns of Human Mobility Through Mobile Phone Data},
  journal   = {{IEEE} Transactions on Mobile Computing},
  year      = {2018},
  volume    = {17},
  number    = {4},
  pages     = {817--830},
  month     = apr,
  doi       = {10.1109/tmc.2017.2742953},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Misc{ThoZhaxxa,
  Title                    = {A prediction approach to representative sampling},

  Author                   = {Ib Thomsen and Li-Chun Zhang},

  File                     = {:ThoZhaxxa - Ib Thomsen and Li-Chun Zhang.pdf:PDF}
}

@Article{ThoSauKnu04a,
  author    = {Wayne E. Thogmartin and John R. Sauer and Melinda G. Knutson},
  title     = {A {HIERARCHICAL} {SPATIAL} {MODEL} {OF} {AVIAN} {ABUNDANCE} {WITH} {APPLICATION} {TO} {CERULEAN} {WARBLERS}},
  journal   = {Ecological Applications},
  year      = {2004},
  volume    = {14},
  number    = {6},
  pages     = {1766--1779},
  month     = dec,
  doi       = {10.1890/03-5247},
  publisher = {Wiley},
}

@Article{Ten18b,
  author    = {Martijn Tennekes},
  title     = {tmap: Thematic Maps in R},
  journal   = {Journal of Statistical Software},
  year      = {2018},
  volume    = {84},
  number    = {6},
  doi       = {10.18637/jss.v084.i06},
  publisher = {Foundation for Open Access Statistic},
}

@TechReport{Ten14a,
  Title                    = {Geographic location of events},
  Author                   = {Martijn Tennekes},
  Institution              = {Statistics Netherlands},
  Year                     = {2014},

  File                     = {:Ten14a - Martijn Tennekes.pdf:PDF}
}

@Article{TaySmiRay10a,
  author    = {Jeff Tayman and Stanley K. Smith and Stefan Rayer},
  title     = {Evaluating Population Forecast Accuracy: A Regression Approach Using County Data},
  journal   = {Population Research and Policy Review},
  year      = {2010},
  volume    = {30},
  number    = {2},
  pages     = {235--262},
  month     = jun,
  doi       = {10.1007/s11113-010-9187-9},
  publisher = {Springer Nature},
}

@InProceedings{TanRowNorMa12a,
  Title                    = {Inferring human mobility patterns from anonymized mobile communication usage},
  Author                   = {Yuzuru Tanahashi and James R. Rowland and Stephen North and Kwan-Liu Ma},
  Booktitle                = {Proceedings of the 10\textsuperscript{th} International Conference on Advances in Mobile Computing {\&} Multimedia - {MoMM} {\textquotesingle}12},
  Year                     = {2012},
  Publisher                = {{ACM} Press},

  Abstract                 = {man movement within a metropolitan area. A better under-
Anonymized Call Detail Records (CDRs) contain positional standing of how, where, and when people move on a daily},
  Doi                      = {10.1145/2428955.2428988},
  File                     = {:TanRowNorMa12a - Yuzuru Tanahashi and James R. Rowland and Stephen North and Kwan-Liu Ma.pdf:PDF},
  Keywords                 = {Due to the assumed physical proximity of a mobile phone Mobile computing, call detail records, human mobility and its user, many researchers have applied anonymized}
}

@Article{TamCla15a,
  author    = {Siu-Ming Tam and Frederic Clarke},
  title     = {Big Data, Official Statistics and Some Initiatives by the Australian Bureau of Statistics},
  journal   = {International Statistical Review},
  year      = {2015},
  volume    = {83},
  number    = {3},
  pages     = {436--448},
  month     = jun,
  doi       = {10.1111/insr.12105},
  publisher = {Wiley},
}

@Article{SorBjeBulBerLanAkhOls18a,
  author    = {Anette {\O}stb{\o} S{\o}rensen and Johannes Bjelland and Heidi Bull-Berg and Andreas Dypvik Landmark and Muhammad Mohsin Akhtar and Nils O.E. Olsson},
  title     = {Use of mobile phone data for analysis of number of train travellers},
  journal   = {Journal of Rail Transport Planning {\&} Management},
  year      = {2018},
  volume    = {8},
  number    = {2},
  pages     = {123--144},
  month     = sep,
  doi       = {10.1016/j.jrtpm.2018.06.002},
  publisher = {Elsevier {BV}},
}

@Article{SunCheGuoLiu05a,
  author    = {Guolin Sun and Jie Chen and Wei Guo and K.J. Ray Liu},
  title     = {Signal processing techniques in network-aided positioning: a survey of state-of-the-art positioning designs},
  journal   = {{IEEE} Signal Processing Magazine},
  year      = {2005},
  volume    = {22},
  number    = {4},
  pages     = {12--23},
  month     = jul,
  booktitle = {IEEE SIGNAL PROCESSING MAGAZINE [12] JULY 2005},
  doi       = {10.1109/msp.2005.1458273},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{StrBraDaa14a,
  author    = {Peter Struijs and Barteld Braaksma and Piet JH Daas},
  title     = {Official statistics and Big Data},
  journal   = {Big Data {\&} Society},
  year      = {2014},
  volume    = {1},
  number    = {1},
  pages     = {205395171453841},
  month     = apr,
  doi       = {10.1177/2053951714538417},
  publisher = {{SAGE} Publications},
}

@InProceedings{SteWolYuXu11a,
  Title                    = {Transportation mode detection using mobile phones and {GIS} information},
  Author                   = {Leon Stenneth and Ouri Wolfson and Philip S. Yu and Bo Xu},
  Booktitle                = {Proceedings of the 19\textsuperscript{th} {ACM} {SIGSPATIAL} International Conference on Advances in Geographic Information Systems - {GIS} {\textquotesingle}11},
  Year                     = {2011},
  Publisher                = {{ACM} Press},

  Abstract                 = {With knowledge of a traveler{\textquoteright}s transportation mode, targeted and},
  Doi                      = {10.1145/2093973.2093982},
  File                     = {:SteWolYuXu11a - Leon Stenneth and Ouri Wolfson and Philip S. Yu and Bo Xu.pdf:PDF},
  Keywords                 = {literature [1, 2, 4, 15, 16]. The existing approaches share the}
}

@InCollection{Ste04a,
  author    = {Charles Steinfield},
  title     = {The development of location based services in mobile commerce},
  booktitle = {E-Life after the Dot Com Bust},
  publisher = {Physica-Verlag {HD}},
  year      = {2004},
  pages     = {177--197},
  doi       = {10.1007/978-3-662-11659-3_10},
}

@Article{StTraNij15a,
  author    = {John Steenbruggen and Emmanouil Tranos and Peter Nijkamp},
  title     = {Data from mobile phone operators: A tool for smarter cities?},
  journal   = {Telecommunications Policy},
  year      = {2015},
  volume    = {39},
  number    = {3-4},
  pages     = {335--346},
  month     = may,
  doi       = {10.1016/j.telpol.2014.04.001},
  publisher = {Elsevier {BV}},
}

@TechReport{SteTraNij14a,
  Title                    = {Data from mobile phone operators A and tool and for smarter cities},
  Author                   = {John Steenbruggen and Emmanouil Tranos and Peter Nijkamp},
  Institution              = {Faculty of Economics and Business Administration. Amsterdam University},
  Year                     = {2014},
  Note                     = {Research Memorandum 2014-1},
  Type                     = {resreport},

  File                     = {:SteTraNij14a - John Steenbruggen and Emmanouil Tranos and Peter Nijkamp.pdf:PDF}
}

@Article{SteBorNijSch11a,
  author    = {John Steenbruggen and Maria Teresa Borzacchiello and Peter Nijkamp and Henk Scholten},
  title     = {Mobile phone data from {GSM} networks for traffic parameter and urban spatial pattern assessment: a review of applications and opportunities},
  journal   = {{GeoJournal}},
  year      = {2011},
  volume    = {78},
  number    = {2},
  pages     = {223--243},
  month     = may,
  doi       = {10.1007/s10708-011-9413-y},
  publisher = {Springer Nature},
}

@TechReport{Spi12a,
  Title                    = {An Overview of Hybrid Location Technologies: Enabling Accurate Everywhere Location},
  Author                   = {Spirent},
  Institution              = {Spirent},
  Year                     = {2012},
  Month                    = nov,
  Note                     = {White Paper},
  Type                     = {resreport},

  File                     = {:Spi12a - Spirent.pdf:PDF}
}

@InProceedings{SotFriMar11a,
  Title                    = {Robust Land Use Characterization of Urban Landscapes using Cell and Phone Data},
  Author                   = {V\'{i}ctor Soto and Enrique Fr\'{\i}as-Mart\'{\i}nez},
  Booktitle                = {Workshop on Pervasive Urban Applications (PURBA)},
  Year                     = {2011},

  Abstract                 = {Mobile devices have become one of the main sensors of hu-
man behavior, and as such, can be used as proxies to study urban envi-
ronments. In this paper we describe a method to automatically identify
land uses from call detail record databases. Given the inherent diversity
of human activities in urban landscapes, we use fuzzy clustering tech-
niques to identify land uses in a robust way, characterizing only those
geographical areas with well defined behaviors. Finally, we validate the
results obtained using expert knowledge.},
  File                     = {:SotFriMar11a - V_'{i}ctor Soto and Enrique Fr_'{_i}as-Mart_'{_i}nez.pdf:PDF}
}

@InCollection{SotFriMarVirFriMar11a,
  author    = {Victor Soto and Vanessa Frias-Martinez and Jesus Virseda and Enrique Frias-Martinez},
  title     = {Prediction of Socioeconomic Levels Using Cell Phone Records},
  booktitle = {User Modeling, Adaption and Personalization},
  publisher = {Springer Berlin Heidelberg},
  year      = {2011},
  pages     = {377--388},
  doi       = {10.1007/978-3-642-22362-4_35},
}

@Article{SonOuyDuWanXio17a,
  author    = {Xin Song and Yuanxin Ouyang and Bowen Du and Jingyuan Wang and Zhang Xiong},
  title     = {Recovering Individual's Commute Routes Based on Mobile Phone Data},
  journal   = {Mobile Information Systems},
  year      = {2017},
  volume    = {2017},
  pages     = {1--11},
  doi       = {10.1155/2017/7653706},
  publisher = {Hindawi Limited},
}

@InCollection{SohVarLaMCheChoSmiConHigGrideL06a,
  author    = {Timothy Sohn and Alex Varshavsky and Anthony LaMarca and Mike Y. Chen and Tanzeem Choudhury and Ian Smith and Sunny Consolvo and Jeffrey Hightower and William G. Griswold and Eyal de Lara},
  title     = {Mobility Detection Using Everyday {GSM} Traces},
  booktitle = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  year      = {2006},
  pages     = {212--224},
  abstract  = {Recognition of everyday physical activities is difficult due to the
challenges of building informative, yet unobtrusive sensors. The most widely 
deployed and used mobile computing device today is the mobile phone, which 
presents an obvious candidate for recognizing activities. This paper explores 
how coarse-grained GSM data from mobile phones can be used to recognize 
high-level properties of user mobility, and daily step count. We demonstrate 
that even without knowledge of observed cell tower locations, we can recognize 
mobility modes that are useful for several application domains. Our mobility 
detection system was evaluated with GSM traces from the everyday lives of 
three data collectors over a period of one month, yielding an overall average ac-
curacy of 85%, and a daily step count number that reasonably approximates the 
numbers determined by several commercial pedometers.},
  doi       = {10.1007/11853565_13},
}

@Article{SohKim06a,
  author    = {W.-S. Soh and H.S. Kim},
  title     = {A Predictive Bandwidth Reservation Scheme Using Mobile Positioning and Road Topology Information},
  journal   = {{IEEE}/{ACM} Transactions on Networking},
  year      = {2006},
  volume    = {14},
  number    = {5},
  pages     = {1078--1091},
  month     = oct,
  doi       = {10.1109/tnet.2006.882899},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Book{Sob94a,
  Title                    = {A primer for the Monte Carlo Method},
  Author                   = {Ilya M. Sobol\textquotesingle},
  Publisher                = {{CRC} {P}ress},
  Year                     = {1994},

  File                     = {:Sobol - 1994 - A Primer for the Monte Carlo Method.pdf:PDF},
  ISBN                     = {0-8493-8673-X}
}

@Article{SmiRob93a,
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  journal = {Journal of the Royal Statistical Society},
  year    = {1993},
  volume  = {55},
  number  = {3-23},
  file    = {:SmiRob93a - {B}ayesian computation via the {G}ibss sampler and related {M}arkov chain {M}onte {C}arlo methods.pdf:PDF},
}

@Article{SinSahPra14a,
  author  = {Balram Singh and Santosh Kumar Sahoo and Soumya Ranjan Pradhan},
  title   = {Analysis of Cellular and Positioning Techniques and in UMTS and Networks},
  journal = {Journal of Telecommunication, Switching Systems and Networks},
  year    = {2014},
  volume  = {1},
  number  = {1},
}

@Article{SilHaiNya09a,
  author    = {Gudeta Sileshi and Girma Hailu and Gerson I. Nyadzi},
  title     = {Traditional occupancy{\textendash}abundance models are inadequate for zero-inflated ecological count data},
  journal   = {Ecological Modelling},
  year      = {2009},
  volume    = {220},
  number    = {15},
  pages     = {1764--1775},
  month     = aug,
  doi       = {10.1016/j.ecolmodel.2009.03.024},
  publisher = {Elsevier {BV}},
}

@Article{SiPiGel15a,
  author    = {Yajuan Si and Natesh S. Pillai and Andrew Gelman},
  title     = {Bayesian Nonparametric Weighted Sampling Inference},
  journal   = {Bayesian Analysis},
  year      = {2015},
  volume    = {10},
  number    = {3},
  pages     = {605--625},
  month     = sep,
  doi       = {10.1214/14-ba924},
  publisher = {Institute of Mathematical Statistics},
}

@Misc{ShuSad12a,
  Title                    = {Secure Multi-Party and Computation (SMC): A Review},

  Author                   = {Samiksha Shukla and G Sadashivappa},
  Year                     = {2012},

  File                     = {:ShuSad12a - Samiksha Shukla and G Sadashivappa.pdf:PDF}
}

@Article{Shi04a,
  author    = {Kazuhiko Shibuya},
  title     = {A Framework of Multi-Agent-Based Modeling, Simulation, and Computational Assistance in an Ubiquitous Environment},
  journal   = {{SIMULATION}},
  year      = {2004},
  volume    = {80},
  number    = {7-8},
  pages     = {367--380},
  month     = jul,
  doi       = {10.1177/0037549704046740},
  publisher = {{SAGE} Publications},
}

@Article{ShiWuChiLiu16a,
  author    = {Li Shi and Lun Wu and Guanghua Chi and Yu Liu},
  title     = {Geographical impacts on social networks from perspectives of space and place: an empirical study using mobile phone data},
  journal   = {Journal of Geographical Systems},
  year      = {2016},
  volume    = {18},
  number    = {4},
  pages     = {359--376},
  month     = sep,
  doi       = {10.1007/s10109-016-0236-8},
  publisher = {Springer Nature},
}

@InProceedings{ShaHuaCasNatIft12a,
  Title                    = {Crowds replace experts: Building better location-based services using mobile social network interactions},
  Author                   = {Pravin Shankar and Yun-Wu Huang and Paul Castro and Badri Nath and Liviu Iftode},
  Booktitle                = {2012 {IEEE} International Conference on Pervasive Computing and Communications},
  Year                     = {2012},
  Month                    = mar,
  Publisher                = {{IEEE}},

  Abstract                 = {Location-based services are growing in popularity As a result, current popular location-based services, such
due to the ubiquity of smartphone users. The relevance of as Google Places (formerly Google Local), Yahoo! Local
location-based query results is very important, especially for and Bing Local, use a combination of several unpublished
mobile phones with limited screen size. Location-based data
frequently changes; this introduces challenges in indexing criteria for ranking places[25]. Further, these criteria are
and ranking places. The growing popularity of mobile social revised periodically so that the systems continue to serve
networks, such as Twitter, FourSquare and Facebook Places, relevant results.
presents an opportunity to build better location-based services An alternate approach used by some location-based ser-
by leveraging user interactions on these networks. In this vices is to rely on experts, for example, Zagat ratings of
paper, we present SocialTelescope, a location-based service that
automatically compiles, indexes and ranks locations, based on restaurants [34]. Such an approach incurs high monetary
user interactions with locations in mobile social networks. We cost. It also lags in timeliness, because the time of review
implemented our system as a location-based search engine that could be several months in the past. It is also susceptible
uses geo-tweets by Twitter users to learn about places. We eval- to expert bias. Another alternate approach, which has seen
uated the coverage and relevance of our system by comparing lot of popularity, is to rely on reviews by all users instead
it against current state-of-the-art approaches including page-
rank (Google Local Search), expert-based (Zagat) and user- of just experts, for example Yelp reviews [31]. Relying
review based (Yelp). Our results show that a crowd-sourced on reviews introduces several problems, such as, how to
location-based service returns results that match those returned distinguish genuine users from marketeers [21] and how to
by current approaches in relevance, at a substantially lower handle negative reviews [32], [33].
cost. Fortunately, people are good judges of the places that they},
  Doi                      = {10.1109/percom.2012.6199845},
  File                     = {:ShaHuaCasNatIft12a - Pravin Shankar and Yun-Wu Huang and Paul Castro and Badri Nath and Liviu Iftode.pdf:PDF}
}

@Article{SevRat10a,
  author    = {Andres Sevtsuk and Carlo Ratti},
  title     = {Does Urban Mobility Have a Daily Routine? Learning from the Aggregate Data of Mobile Networks},
  journal   = {Journal of Urban Technology},
  year      = {2010},
  volume    = {17},
  number    = {1},
  pages     = {41--60},
  month     = apr,
  doi       = {10.1080/10630731003597322},
  publisher = {Informa {UK} Limited},
}

@InProceedings{SenDem16a,
  Title                    = {When mobile network operators and statistical offices meet - integrating mobile positioning data into the production process of tourism statistics},
  Author                   = {Gerdy Senaeve and Christophe Demunter},
  Booktitle                = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  Year                     = {2016},

  Address                  = {Venice, Italy},
  Month                    = nov,

  File                     = {:SenDem16a - Gerdy Senaeve and Christophe Demunter.pdf:PDF},
  Keywords                 = {big data, mobile phone, mobile positioning, signalling, tourism statistics}
}

@Article{SebRam71a,
  author   = {P. Sebastiani and M. Ramoni},
  title    = {On the Use of Bayesian Networks to Analyze Survey Data},
  journal  = {Research in Official Statistics},
  year     = {1971},
  volume   = {4},
  number   = {1},
  pages    = {53--64},
  keywords = {Automated modeling, Bayesian networks, graphical models, Bayesian model selection},
}

@Article{Sch99a,
  author    = {A. A. Schuessler},
  title     = {Ecological inference},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {1999},
  volume    = {96},
  number    = {19},
  pages     = {10578--10581},
  month     = sep,
  doi       = {10.1073/pnas.96.19.10578},
  file      = {:Sch99a - Ecological Inference.pdf:PDF},
  publisher = {Proceedings of the National Academy of Sciences},
}

@Article{SchSoeKapCou09a,
  author    = {Matthias Schonlau and Arthur van Soest and Arie Kapteyn and Mick Couper},
  title     = {Selection Bias in Web Surveys and the Use of Propensity Scores},
  journal   = {Sociological Methods {\&} Research},
  year      = {2009},
  volume    = {37},
  number    = {3},
  pages     = {291--318},
  month     = feb,
  abstract  = {Web surveys are a popular survey mode, but the subpopulation with Internet access may not represent the population of interest. The authors investigate whether adjusting using weights or matching on a small set of variables makes the distributions of target variables representative of the population. This application has a rich sampling design; the Internet sample is part of an existing probability sample, the Health and Retirement Study, that is representative of the U.S. population aged 50 and older. For the dichotomous variables investigated, the adjustment helps. On average, the sample means in the Internet access sample differ by 6.5 percent before and 3.7 percent after adjustment. Still, a large number of adjusted estimates remain significantly different from their target estimates based on the complete sample. This casts doubt on the common procedure to use only a few variables to correct for the selectivity of convenience samples.},
  doi       = {10.1177/0049124108327128},
  publisher = {{SAGE} Publications},
}

@InCollection{SchAxh04a,
  author    = {Stefan Sch{\"{o}}nfelder and Kay W. Axhausen},
  title     = {On the Variability of Human Activity Spaces},
  booktitle = {The Real and Virtual Worlds of Spatial Planning},
  publisher = {Springer Berlin Heidelberg},
  year      = {2004},
  pages     = {237--262},
  doi       = {10.1007/978-3-662-10398-2_17},
}

@TechReport{SchAxh02a,
  Title                    = {Measuring the size and structure of human activity spaces: The longitudinal perspective: ETC 2002 - poster session},
  Author                   = {Sch{\"{o}}nfelder, Stefan and Axhausen, Kay W.},
  Institution              = {ETH Zurich},
  Year                     = {2002},

  Doi                      = {10.3929/ethz-a-004444846},
  File                     = {:SchAxh02a - Sch{__{o}}nfelder, Stefan and Axhausen, Kay W..pdf:PDF},
  Keywords                 = {info:eu-repo/classification/ddc/624, SPATIAL MOBILITY (GEOGRAPHY), GEOGRAFISCHE INFORMATIONSSYSTEME, info:eu-repo/classification/ddc/380, Activity space, Civil engineering, ETH Zurich, ERHEBUNGSVERFAHREN (SOZIALWISSENSCHAFTEN), Longitudinal travel data, info:eu-repo/classification/ddc/550, Commerce, communications, transport, Earth sciences, Mobidrive, Institute for Transport Planning and Systems (IVT), R{{\"{A}}}UMLICHE MOBILIT{{\"{A}}}T (GEOGRAFIE), GEOGRAPHICAL INFORMATION SYSTEM, SURVEY METHODS (SOCIAL SCIENCES), Development of measures},
  Language                 = {en},
  Publisher                = {ETH Zurich}
}

@Book{Sch03a,
  Title                    = {Mobile Communications},
  Author                   = {Jochen H. Schiller},
  Publisher                = {Addison-Wesley},
  Year                     = {2003},

  Address                  = {London, UK},
  Edition                  = {2\textsuperscript{nd}},

  File                     = {:Schiller - 2003 - Mobile Communications - 2nd ed.pdf:PDF}
}

@Book{SchVoi04a,
  Title                    = {Location-based services},
  Author                   = {Jochen Schiller and Agn\`{e}s Voisard},
  Publisher                = {Elsevier},
  Year                     = {2004},

  File                     = {:Schiller and Voisard - 2004 - Location-based services.pdf:PDF},
  ISBN                     = {1-55860-929-6}
}

@Article{SarBreBurWehZivAlvHam17a,
  author  = {Carlos Sarraute and Jorge Brea and Javier Burroni and Klaus Wehmuth and Artur Ziviani and Jos{\'e} Ignacio Alvarez-Hamelin},
  title   = {Social Events in a Time-Varying Mobile Phone Graph},
  journal = {CoRR},
  year    = {2017},
}

@Article{SanBraAug95a,
  author    = {Eva S{\'{a}}nchez and Rafael Bravo de la Parra and Pierre Auger},
  title     = {Linear discrete models with different time scales},
  journal   = {Acta Biotheoretica},
  year      = {1995},
  volume    = {43},
  number    = {4},
  pages     = {465--476},
  month     = dec,
  doi       = {10.1007/bf00713565},
  keywords  = {Approximate aggregation of variables, population dynamics, perturbations, time scales, eigenvalues and eigenvectors analysis},
  publisher = {Springer Nature},
}

@InProceedings{SafMesFer13a,
  Title                    = {ATLAS Project -- Developing a mobile-based travel survey},
  Author                   = {Hamid Safi and Mahmoud Mesbah and Luis Ferreira},
  Booktitle                = {Australasian Transport Research Forum 2013 Proceedings},
  Year                     = {2013},

  Address                  = {Brisbane, Australia},
  Month                    = oct,

  Abstract                 = {Travel data collection has always been considered as a fundamental part of all transport 
planning studies, and there has been a continuous effort to employ new approaches in order 
to increase the accuracy of collected data and reflect the real behaviour of individuals. Many 
approaches have been utilized for performing travel surveys, but there are still significant 
areas for improvement, as they need considerable financial and human resources, have an 
insufficient time-coverage and mostly engage respondents considerably, which sometimes 
implies biased results.},
  File                     = {:SafMesFer13a - Hamid Safi and Mahmoud Mesbah and Luis Ferreira.pdf:PDF},
  Url                      = {http://www.atrf.info/papers/2013/index.aspx}
}

@Article{RuiUreGarPerVilGar13a,
  author    = {Daniel Ruiz and Jes{\'{u}}s Ure{\~{n}}a and Juan C. Garc{\'{\i}}a and Carmen P{\'{e}}rez and Jos{\'{e}} M. Villadangos and Enrique Garc{\'{\i}}a},
  title     = {Efficient trilateration algorithm using time differences of arrival},
  journal   = {Sensors and Actuators A: Physical},
  year      = {2013},
  volume    = {193},
  pages     = {220--232},
  month     = apr,
  doi       = {10.1016/j.sna.2012.12.021},
  publisher = {Elsevier {BV}},
}

@Article{RueMarCho09a,
  author    = {H{\aa}vard Rue and Sara Martino and Nicolas Chopin},
  title     = {Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations},
  journal   = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
  year      = {2009},
  volume    = {71},
  number    = {2},
  pages     = {319--392},
  month     = apr,
  doi       = {10.1111/j.1467-9868.2008.00700.x},
  keywords  = {Approximate Bayesian inference; Gaussian Markov random fields; Generalized additive mixed models; Laplace approximation; Parallel computing; Sparse matrices; Structured additive regression models},
  publisher = {Wiley},
}

@Article{RueMar07a,
  author    = {H{\AA}vard Rue and Sara Martino},
  title     = {Approximate Bayesian inference for hierarchical Gaussian Markov random field models},
  journal   = {Journal of Statistical Planning and Inference},
  year      = {2007},
  volume    = {137},
  number    = {10},
  pages     = {3177--3192},
  month     = oct,
  doi       = {10.1016/j.jspi.2006.07.016},
  publisher = {Elsevier {BV}},
}

@Misc{RobKleJut15a,
  Title                    = {Public-Private Partnerships for Statistics Lessons Learned, Future Steps},

  Author                   = {Nicholas Robin and Thilo Klein and Johannes J\"{u}tting},
  HowPublished             = {PARIS21 Partnership in Statistics for Development in the 21\textsuperscript{st} Century Discussion Paper No. 8},
  Month                    = dec,
  Year                     = {2015},

  File                     = {:RobKleJut15a - Nicholas Robin and Thilo Klein and Johannes J__{u}tting.pdf:PDF}
}

@InProceedings{RobWra09a,
  Title                    = {Computational methods for Bayesian model choice},
  Author                   = {C. P. Robert and D. Wraith},
  Booktitle                = {AIP Conference Proceedings},
  Year                     = {2009},
  Editor                   = {Paul M. Goggans and Chun-Yong Chan},
  Number                   = {251},
  Publisher                = {{AIP}},
  Volume                   = {1193},

  Doi                      = {10.1063/1.3275622},
  File                     = {:RobWra09a - C. P. Robert and D. Wraith.pdf:PDF}
}

@Book{RobCas10a,
  Title                    = {Introducing Monte Carlo Methods with R},
  Author                   = {Christian P. Robert and George Casella},
  Publisher                = {Springer},
  Year                     = {2010},

  File                     = {:Robert and Casella - 2010 - Introducing Monte Carlo Methods with R.pdf:PDF}
}

@Article{Rob16a,
  author  = {Christian P. Robert},
  title   = {The Metropolis-Hastings Algorithm},
  journal = {Wiley StatsRef: Statistics Reference Online},
  year    = {2016},
  doi     = {10.1002/9781118445112.stat07834},
}

@Article{RobBol12a,
  author    = {Christian Robert and William M. Boldstad},
  title     = {Understanding Computational Bayesian Statistics},
  journal   = {{CHANCE}},
  year      = {2012},
  volume    = {25},
  number    = {2},
  pages     = {57--58},
  month     = apr,
  doi       = {10.1080/09332480.2012.685375},
  publisher = {Informa {UK} Limited},
}

@Article{RiccWidPanCra17a,
  author    = {Fabio Ricciato and Peter Widhalm and Francesco Pantisano and Massimo Craglia},
  title     = {Beyond the {\textquotedblleft}single-operator, {CDR}-only{\textquotedblright} paradigm: An interoperable framework for mobile phone network data analyses and population density estimation},
  journal   = {Pervasive and Mobile Computing},
  year      = {2017},
  volume    = {35},
  pages     = {65--82},
  month     = feb,
  doi       = {10.1016/j.pmcj.2016.04.009},
  publisher = {Elsevier {BV}},
}

@InProceedings{RicDeMWirSeySka18a,
  Title                    = {Processing of Mobile Network Operator data for Official Statistics: the case for public-private partnerships},
  Author                   = {Fabio Ricciato and Freddy De Meersman and Albrecht Wirthmann and Gerdy Seynaeve and Michail Skaliotis},
  Booktitle                = {DGINS18 Conference},
  Year                     = {2018},

  Abstract                 = {This paper discusses various aspects related to the potential partnership between Statistical},
  Doi                      = {ng},
  File                     = {:RicDeMWirSeySka18a - Fabio Ricciato and Freddy De Meersman and Albrecht Wirthmann and Gerdy Seynaeve and Michail Skaliotis.pdf:PDF}
}

@InProceedings{Ric18a,
  author    = {Fabio Ricciato},
  title     = {Towards a Reference Methodological Framework for processing MNO data for Official Statistics},
  booktitle = {15\textsuperscript{th} World Forum on Tourism Statistics},
  year      = {2018},
  number    = {opera-},
  abstract  = {Mobile network signalling data, captured from the continuous interaction of mobile termi-},
}

@Article{RheShiHonLeeKimCho11a,
  author    = {Injong Rhee and Minsu Shin and Seongik Hong and Kyunghan Lee and Seong Joon Kim and Song Chong},
  title     = {On the Levy-Walk Nature of Human Mobility},
  journal   = {{IEEE}/{ACM} Transactions on Networking},
  year      = {2011},
  volume    = {19},
  number    = {3},
  pages     = {630--643},
  month     = jun,
  doi       = {10.1109/tnet.2011.2120618},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@TechReport{ResRomMai05a,
  Title                    = {Global Positioning in Harsh Environments},
  Author                   = {Bernd Resch and Peter Romirer-Maierhofer},
  Institution              = {School of Information Science, Computer and Electrical Engineering, Halmstad University},
  Year                     = {2005},

  File                     = {:ResRomMai05a - Bernd Resch and Peter Romirer-Maierhofer.pdf:PDF}
}

@Misc{ReiKou15a,
  Title                    = {The Proliferation of {\textquotedblleft}Big Data{\textquotedblright} and Implications for Official Statistics and Statistical Agencies},

  Author                   = {Christian Reimsbach-Kounatze},
  HowPublished             = {OECD Digital Economy Papers No. 245},
  Month                    = jan,
  Year                     = {2015},

  Doi                      = {10.1787/5js7t9wqzvg8-en},
  File                     = {:ReiKou15a - Christian Reimsbach-Kounatze.pdf:PDF},
  Publisher                = {Organisation for Economic Co-Operation and Development ({OECD})}
}

@Article{ReiCox2015a,
  author    = {Nancy Reid and David R. Cox},
  title     = {On Some Principles of Statistical Inference},
  journal   = {International Statistical Review},
  year      = {2015},
  volume    = {83},
  number    = {2},
  pages     = {293--308},
  month     = oct,
  doi       = {10.1111/insr.12067},
  publisher = {Wiley},
}

@Article{ReiZabHol17a,
  author    = {Giles Reid and Felipa Zabala and Anders Holmberg},
  title     = {Extending {TSE} to Administrative Data: A Quality Framework and Case Studies from Stats {NZ}},
  journal   = {Journal of Official Statistics},
  year      = {2017},
  volume    = {33},
  number    = {2},
  pages     = {477--511},
  month     = jun,
  doi       = {10.1515/jos-2017-0023},
  publisher = {Walter de Gruyter {GmbH}},
}

@Article{RehBat15a,
  author  = {Muhammad Habib~ur~Rehman and Aisha Batool},
  title   = {Pattern-based Data Sharing in Big Data Environments},
  journal = {Digital Technologies},
  year    = {2015},
  volume  = {1},
  number  = {1},
  pages   = {39--42},
  doi     = {10.12691/dt-1-1-8},
}

@Article{RegMayDugKopLasModMonSalSul09a,
  author    = {W.C. Regli and I. Mayk and C.J. Dugan and J.B. Kopena and R.N. Lass and P.J. Modi and W.M. Mongan and J.K. Salvage and E.A. Sultanik},
  title     = {Development and Specification of a Reference Model for Agent-Based Systems},
  journal   = {{IEEE} Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)},
  year      = {2009},
  volume    = {39},
  number    = {5},
  pages     = {572--596},
  month     = sep,
  doi       = {10.1109/tsmcc.2009.2020507},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{RavCasBro16a,
  author    = {Don van Ravenzwaaij and Pete Cassey and Scott D. Brown},
  title     = {A simple introduction to Markov Chain Monte{\textendash}Carlo sampling},
  journal   = {Psychonomic Bulletin {\&} Review},
  year      = {2016},
  volume    = {25},
  number    = {1},
  pages     = {143--154},
  month     = mar,
  doi       = {10.3758/s13423-016-1015-8},
  publisher = {Springer Nature},
}

@Article{RauAhaTir16a,
  author    = {Janika Raun and Rein Ahas and Margus Tiru},
  title     = {Measuring tourism destinations using mobile tracking data},
  journal   = {Tourism Management},
  year      = {2016},
  volume    = {57},
  pages     = {202--212},
  month     = dec,
  doi       = {10.1016/j.tourman.2016.06.006},
  publisher = {Elsevier {BV}},
}

@InProceedings{RauAha16a,
  Title                    = {Defining usual environment with mobile tracking data},
  Author                   = {Janika Raun and Rein Ahas},
  Booktitle                = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  Year                     = {2016},

  Address                  = {Venices, Italy},
  Month                    = nov,

  File                     = {:RauAha16a - Janika Raun and Rein Ahas.pdf:PDF},
  Keywords                 = {domestic tourism, usual environment; mobile positioning, GPS}
}

@Article{RasTur15a,
  author    = {Haroon Rashid and Ashok Kumar Turuk},
  title     = {Dead reckoning localisation technique for mobile wireless sensor networks},
  journal   = {{IET} Wireless Sensor Systems},
  year      = {2015},
  volume    = {5},
  number    = {2},
  pages     = {87--96},
  month     = apr,
  doi       = {10.1049/iet-wss.2014.0043},
  publisher = {Institution of Engineering and Technology ({IET})},
}

@Article{Rao11a,
  author    = {J. N. K. Rao},
  title     = {Impact of Frequentist and Bayesian Methods on Survey Sampling Practice: A Selective Appraisal},
  journal   = {Statistical Science},
  year      = {2011},
  volume    = {26},
  number    = {2},
  pages     = {240--256},
  month     = may,
  doi       = {10.1214/10-sts346},
  publisher = {Institute of Mathematical Statistics},
}

@Article{RamGalGarMouTalMarRegBolCanAloBetBenHer2015a,
  author    = {Sergio Ram{\'{\i}}rez-Gallego and Salvador Garc{\'{\i}}a and H{\'{e}}ctor Mouri{\~{n}}o-Tal{\'{\i}}n and David Mart{\'{\i}}nez-Rego and Ver{\'{o}}nica Bol{\'{o}}n-Canedo and Amparo Alonso-Betanzos and Jos{\'{e}} Manuel Ben{\'{\i}}tez and Francisco Herrera},
  title     = {Data discretization: taxonomy and big data challenge},
  journal   = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
  year      = {2015},
  volume    = {6},
  number    = {1},
  pages     = {5--21},
  month     = nov,
  doi       = {10.1002/widm.1173},
  publisher = {Wiley},
}

@Article{RamHew05a,
  author    = {Charles A. Ramsey and Alan D. Hewitt},
  title     = {A Methodology for Assessing Sample Representativeness},
  journal   = {Environmental Forensics},
  year      = {2005},
  volume    = {6},
  number    = {1},
  pages     = {71--75},
  month     = mar,
  doi       = {10.1080/15275920590913877},
  publisher = {Informa {UK} Limited},
}

@InProceedings{RaiAliLoyWir11a,
  Title                    = {Estimation of base station position using timing advance measurements},
  Author                   = {Matti Raitoharju and Simo Ali-L{\"{o}}ytty and Lauri Wirola},
  Booktitle                = {International Conference on Graphic and Image Processing ({ICGIP} 2011)},
  Year                     = {2011},
  Month                    = oct,
  Publisher                = {{SPIE}},

  Abstract                 = {Timing Advance is used in TDMA (Time Division Arrival), TDOA (Time Difference of Arrival), among others.
Multiple Access) systems, such as GSM and LTE, to For a comprehensive study of these methods see [2]. 
synchronize the mobile phone to the cellular BS (Base Station). If the handset has WLAN (Wireless Local Area 
Mobile phone positioning can use TA measurements if BS Network) capabilities, the cell positioning may be done 
positions are known, but in many cases BS positions are not in exploiting heard WLAN stations. WLAN BS has a 
the public domain. In this work we study how to use a set of significantly smaller range than GSM BS, and this leads to 
TA measurements taken by mobile phones at known positions better positioning accuracy. Problems with WLAN cell 
to estimate the position of a BS. This paper describes two positioning are the scarcity of WLANs in rural areas and the 
methods -- GMF (Gaussian Mixture Filter) and PMF (Point possibility that WLAN BSs may be mobile. Mapping of 
Mass Filter) for estimation of the BS position. Positioning},
  Doi                      = {10.1117/12.913427},
  File                     = {:RaiAliLoyWir11a - Matti Raitoharju and Simo Ali-L{__{o}}ytty and Lauri Wirola.pdf:PDF},
  Keywords                 = {- Timing advance; Nonlinear filters; Mobile are large and for some reason GNSS is not available. communication; Position measurement; Positioning; GSM; However, for the method to work, it is necessary to know the}
}

@Article{RaiLytJac06a,
  author    = {Steven F. Railsback and Steven L. Lytinen and Stephen K. Jackson},
  title     = {Agent-based Simulation Platforms: Review and Development Recommendations},
  journal   = {{SIMULATION}},
  year      = {2006},
  volume    = {82},
  number    = {9},
  pages     = {609--623},
  month     = sep,
  doi       = {10.1177/0037549706073695},
  publisher = {{SAGE} Publications},
}

@Article{Rad18a,
  author    = {Walter J. Radermacher},
  title     = {Official statistics in the era of big data opportunities and threats},
  journal   = {International Journal of Data Science and Analytics},
  year      = {2018},
  volume    = {6},
  number    = {3},
  pages     = {225--231},
  month     = apr,
  doi       = {10.1007/s41060-018-0124-z},
  publisher = {Springer Nature America, Inc},
}

@Article{QinShaSonTan18a,
  author    = {Tian Qin and Wufan Shangguan and Guojie Song and Jie Tang},
  title     = {Spatio-Temporal Routine Mining on Mobile Phone Data},
  journal   = {{ACM} Transactions on Knowledge Discovery from Data},
  year      = {2018},
  volume    = {12},
  number    = {5},
  pages     = {1--24},
  month     = jun,
  doi       = {10.1145/3201577},
  publisher = {Association for Computing Machinery ({ACM})},
}

@Article{PuLiuXuQuNi14a,
  author    = {Jiansu Pu and Siyuan Liu and Panpan Xu and Huamin Qu and Lionel M. Ni},
  title     = {{MViewer}: mobile phone spatiotemporal data viewer},
  journal   = {Frontiers of Computer Science},
  year      = {2014},
  volume    = {8},
  number    = {2},
  pages     = {298--315},
  month     = jan,
  doi       = {10.1007/s11704-013-3009-2},
  publisher = {Springer Nature},
}

@Article{PotEli06a,
  author    = {Joanne M. Potts and Jane Elith},
  title     = {Comparing species abundance models},
  journal   = {Ecological Modelling},
  year      = {2006},
  volume    = {199},
  number    = {2},
  pages     = {153--163},
  month     = nov,
  doi       = {10.1016/j.ecolmodel.2006.05.025},
  publisher = {Elsevier {BV}},
}

@Article{PonSarMinTraZivSal16a,
  author  = {Nicolas B. Ponieman and Carlos Sarraute and Martin Minnoni and Matias Travizano and Pablo Rodriguez Zivic and Alejo Salles},
  title   = {Mobility and sociocultural events in mobile phone data records},
  journal = {AI Communications},
  year    = {2016},
  volume  = {29},
  number  = {1},
  pages   = {77--86},
  doi     = {10.3233/AIC-150687},
}

@Article{PicRuiLenRamDubFriMar15a,
  author    = {Miguel Picornell and Tom{\'{a}}s Ruiz and Maxime Lenormand and Jos{\'{e}} J. Ramasco and Thibaut Dubernet and Enrique Fr{\'{\i}}as-Mart{\'{\i}}nez},
  title     = {Exploring the potential of phone call data to characterize the relationship between social network and travel behavior},
  journal   = {Transportation},
  year      = {2015},
  volume    = {42},
  number    = {4},
  pages     = {647--668},
  month     = mar,
  doi       = {10.1007/s11116-015-9594-1},
  publisher = {Springer Nature},
}

@Article{PhiSmoOli12a,
  author    = {Santi Phithakkitnukoon and Zbigniew Smoreda and Patrick Olivier},
  title     = {Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data},
  journal   = {{PLoS} {ONE}},
  year      = {2012},
  volume    = {7},
  number    = {6},
  pages     = {e39253},
  month     = jun,
  doi       = {10.1371/journal.pone.0039253},
  editor    = {Yamir Moreno},
  publisher = {Public Library of Science ({PLoS})},
}

@InProceedings{PetEckLehWorMel02a,
  Title                    = {An experimental evaluation of network-based methods for mobile station positioning},
  Author                   = {M. Pettersen and R. Eckhoff and P.H. Lehne and T.A. Worren and E. Melby},
  Booktitle                = {The 13\textsuperscript{th} {IEEE} International Symposium on Personal, Indoor and Mobile Radio Communications},
  Year                     = {2002},
  Publisher                = {{IEEE}},

  Abstract                 = {- Different methods for network-based mobile
positioning were compared experimentally. The Cell-id and A. Cell-id and TA},
  Doi                      = {10.1109/pimrc.2002.1046552},
  File                     = {:PetEckLehWorMel02a - M. Pettersen and R. Eckhoff and P.H. Lehne and T.A. Worren and E. Melby.pdf:PDF},
  Keywords                 = {-- Location technology, positioning, propagation current TA value. The angles are fixed for each cell and are}
}

@PhdThesis{PerRos14a,
  Title                    = {Evaluation of the LTE positioning capabilities in realistic navigation channels},
  Author                   = {Jos\'{e} A. del Peral-Rosado},
  School                   = {Dept. Telecommunications and Systems Engineering. Universitat Aut\`{o}noma de Barcelona},
  Year                     = {2014},

  File                     = {:PerRos14a - Jos_'{e} A. del Peral-Rosado.pdf:PDF}
}

@Article{PelGorHel16a,
  author    = {Mathias Pelka and Grigori Goronzy and Horst Hellbr{\"{u}}ck},
  title     = {Iterative approach for anchor configuration of positioning systems},
  journal   = {{ICT} Express},
  year      = {2016},
  volume    = {2},
  number    = {1},
  pages     = {1--4},
  month     = mar,
  doi       = {10.1016/j.icte.2016.02.009},
  publisher = {Elsevier {BV}},
}

@Article{PejSim15a,
  author    = {Predrag Pejovi{\'{c}} and Mirjana Simi{\'{c}}},
  title     = {Improving precision of mobile positioning in highway environments},
  journal   = {Annals of Telecommunications - Annales des T{\'{e}}l{\'{e}}communications},
  year      = {2015},
  volume    = {70},
  number    = {11-12},
  pages     = {491--500},
  month     = jun,
  doi       = {10.1007/s12243-015-0470-y},
  publisher = {Springer Nature},
}

@Article{PeiSobRatShaLiZho14a,
  author    = {Tao Pei and Stanislav Sobolevsky and Carlo Ratti and Shih-Lung Shaw and Ting Li and Chenghu Zhou},
  title     = {A new insight into land use classification based on aggregated mobile phone data},
  journal   = {International Journal of Geographical Information Science},
  year      = {2014},
  volume    = {28},
  number    = {9},
  pages     = {1988--2007},
  month     = may,
  doi       = {10.1080/13658816.2014.913794},
  publisher = {Informa {UK} Limited},
}

@Article{PeaOlvPor16a,
  author    = {John W. Pearson and Sheehan Olver and Mason A. Porter},
  title     = {Numerical methods for the computation of the confluent and Gauss hypergeometric functions},
  journal   = {Numerical Algorithms},
  year      = {2016},
  volume    = {74},
  number    = {3},
  pages     = {821--866},
  month     = aug,
  doi       = {10.1007/s11075-016-0173-0},
  publisher = {Springer Nature},
}

@Article{ParHon11a,
  author    = {Chee-Hyun Park and Kwang-Seok Hong},
  title     = {Block {LMS}-based source localization using range measurement},
  journal   = {Digital Signal Processing},
  year      = {2011},
  volume    = {21},
  number    = {2},
  pages     = {367--374},
  month     = mar,
  doi       = {10.1016/j.dsp.2010.06.014},
  publisher = {Elsevier {BV}},
}

@InProceedings{ParDinDasPalSer13a,
  Title                    = {Identification and Characterization of Human Behavior Patterns from Mobile Phone Data},
  Author                   = {P. Paraskevopoulos and T.-C. Dinh and Z. Dashdorj and T. Palpanas and L. Serafini},
  Booktitle                = {Proc. NetMob D4D Challenge},
  Year                     = {2013},
  Month                    = may,
  Pages                    = {1--13},

  Abstract                 = {In order to achieve the above goals, we need to complement
The availability of datasets coming from the telecommuni- the information present in the D4D datasets with contextual
cations industry, and specifically those relevant to the use information that describes the environment and context in
of mobile phones, are helping to conduct studies on the pat- which a user is making a phone call, and that can provide an
terns that appear at large scales, and to better understand additional set of feature for the characterization of the user
social behaviors. This study aims at developing methods for behavior. Information about the context of a call can be ex-
enabling the extraction and characterization of normal be- tracted from other sources on the web, like event databases,
havior patterns, and the identification of exceptional, or di- weather forecast database, etc.
vergent behaviors. We study call activity and mobility pat-
terns to classify the observed behaviors that exhibit similar In this work, we study the call activity and mobility pat-
characteristics, and we analyze and characterize the anoma- terns, classify the observed behaviors that exhibit similar
lous behaviors. Moreover, we link the identified behaviors characteristics, and we analyze and characterize the anoma-
to important events (e.g., national and religious holidays) lous behaviors. The results of our work can be used for
that took place in the same time period, and examine the early identification of exceptional situations, monitoring the
interplay between the behaviors we observe and the nature effects of important events in large areas, urban and trans-
of these events. The results of our work could be used for portation planning, and others.
early identification of exceptional situations, monitoring the
effects of important events in large areas, urban and trans- This paper is organized as follows. The next section briefly
portation planning, and others. discusses related works. Section 3 describes D4D datasets},
  File                     = {:ParDinDasPalSer13a - P. Paraskevopoulos and T.-C. Dinh and Z. Dashdorj and T. Palpanas and L. Serafini.pdf:PDF}
}

@Article{PapVanGabSmoPedGia16a,
  author    = {Luca Pappalardo and Maarten Vanhoof and Lorenzo Gabrielli and Zbigniew Smoreda and Dino Pedreschi and Fosca Giannotti},
  title     = {An analytical framework to nowcast well-being using mobile phone data},
  journal   = {International Journal of Data Science and Analytics},
  year      = {2016},
  volume    = {2},
  number    = {1-2},
  pages     = {75--92},
  month     = jun,
  doi       = {10.1007/s41060-016-0013-2},
  publisher = {Springer Nature},
}

@Article{PanTizBajSmoCol17a,
  author    = {Cecilia Panigutti and Michele Tizzoni and Paolo Bajardi and Zbigniew Smoreda and Vittoria Colizza},
  title     = {Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models},
  journal   = {Royal Society Open Science},
  year      = {2017},
  volume    = {4},
  number    = {5},
  pages     = {160950},
  month     = may,
  doi       = {10.1098/rsos.160950},
  publisher = {The Royal Society},
}

@Article{PalEsoBarChuOzgLi12a,
  author    = {John R. B. Palmer and Thomas J. Espenshade and Frederic Bartumeus and Chang Y. Chung and Necati Ercan Ozgencil and Kathleen Li},
  title     = {New Approaches to Human Mobility: Using Mobile Phones for Demographic Research},
  journal   = {Demography},
  year      = {2012},
  volume    = {50},
  number    = {3},
  pages     = {1105--1128},
  month     = nov,
  doi       = {10.1007/s13524-012-0175-z},
  publisher = {Springer Nature},
}

@InProceedings{DaaPutBuevdH13a,
  Title                    = {Big Data and Official Statistics},
  Author                   = {Daas P.J.H and Puts M.J and Buelens B and van den Hurk P.A.M},
  Booktitle                = {New Technologies and Techniques in Statistics},
  Year                     = {2013},

  File                     = {:DaaPutBuevdH13a - Daas P.J.H and Puts M.J and Buelens B and van den Hurk P.A.M.pdf:PDF},
  Keywords                 = {Large data sets, Traffic data, Social media Acknowledgements: The research described in this paper would not have been possible without the support of many people. The authors particularly wish to express their gratitude to Martijn Tennekes, Edwin de Jonge, Barteld Braaksma, Floris van Ruth and Marko Roos for their stimulating discussions on Big Data and official statistics. 1. Introduction In our modern world more and more data are generated on the web and produced by sensors in the ever growing number of electronic devices surrounding us. The amount of data and the frequency at which they are produced have led to the introduction of the term {\textquoteleft}Big Data{\textquoteright} (Lynch 2008). These are data sources that can be --generally-- described as: {\textquotedblleft}high volume, velocity and variety of data that demand cost-effective, innovative forms of processing for enhanced insight and decision making{\textquotedblright}. This is a variant of the definition proposed by Gartner (2012). More on Big Data and their innovative potential can be found in the McKinsey report (Manyika et al. 2011). In addition to generating new commercial opportunities in the private sector, Big Data are potentially a very interesting data source for official statistics; either for use on their own, or in combination with more traditional data sources such as sample surveys and}
}

@Article{OstKieLin16a,
  author    = {Gerald Ostermayer and Christoph Kieslich and Manuel Lindorfer},
  title     = {Trajectory estimation based on mobile network operator data for cellular network simulations},
  journal   = {{EURASIP} Journal on Wireless Communications and Networking},
  year      = {2016},
  volume    = {2016},
  number    = {1},
  month     = oct,
  doi       = {10.1186/s13638-016-0718-x},
  publisher = {Springer Nature},
}

@Article{OnnSarHyvSzaLazKasKerBar07a,
  author    = {J.-P. Onnela and J. Saramaki and J. Hyvonen and G. Szabo and D. Lazer and K. Kaski and J. Kertesz and A.-L. Barabasi},
  title     = {Structure and tie strengths in mobile communication networks},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {2007},
  volume    = {104},
  number    = {18},
  pages     = {7332--7336},
  month     = apr,
  doi       = {10.1073/pnas.0610245104},
  publisher = {Proceedings of the National Academy of Sciences},
}

@Misc{Obe08a,
  Title                    = {Self-selection bias versus nonresponse bias in the Perceptions of Mobility survey},

  Author                   = {Daniel Oberski},
  HowPublished             = {The Netherlands Institute for Social Research},
  Month                    = feb,
  Year                     = {2008},

  File                     = {:Obe08a - Daniel Oberski.pdf:PDF},
  Url                      = {978 90 377 0343 6}
}

@InCollection{NurBha08a,
  author    = {Petteri Nurmi and Sourav Bhattacharya},
  title     = {Identifying Meaningful Places: The Non-parametric Way},
  booktitle = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  year      = {2008},
  editor    = {J. Indulska and others},
  volume    = {5013},
  series    = {LNCS},
  pages     = {111--127},
  abstract  = {Gathering and analyzing location data is an important part
of many ubiquitous computing applications. The most common way to
represent location information is to use numerical coordinates, e.g., lat-
itudes and longitudes. A problem with this approach is that numerical
coordinates are usually meaningless to a user and they contrast with the
way humans refer to locations in daily communication. Instead of using
coordinates, humans tend to use descriptive statements about their lo-
cation; for example, {\textquotedblright}I{\textquoteright}m home{\textquotedblright} or {\textquotedblright}I{\textquoteright}m at Starbucks.{\textquotedblright} Locations, to
which a user can attach meaningful and descriptive semantics, are of-
ten called places. In this paper we focus on the automatic extraction of
places from discontinuous GPS measurements. We describe and evaluate
a non-parametric Bayesian approach for identifying places from this kind
of data. The main novelty of our approach is that the algorithm is fully
automated and does not require any parameter tuning. Another novel
aspect of our algorithm is that it can accurately identify places without
temporal information. We evaluate our approach using data that has
been gathered from different users and different geographic areas. The
traces that we use exhibit different characteristics and contain data from
daily life as well as from traveling abroad. We also compare our algo-
rithm against the popular k-means algorithm. The results indicate that
our method can accurately identify meaningful places from a variety of
location traces and that the algorithm is robust against noise.},
  doi       = {10.1007/978-3-540-79576-6_7},
}

@TechReport{Nur09a,
  Title                    = {Identifying Meaningful Places},
  Author                   = {Petteri Nurmi},
  Institution              = {Faculty of Science, University of Helsinki},
  Year                     = {2009},

  File                     = {:Nur09a - Petteri Nurmi.pdf:PDF}
}

@InProceedings{Nur16a,
  Title                    = {Improving the accuracy of outbound tourism statistics with mobile positioning data},
  Author                   = {Ossi Nurmi},
  Booktitle                = {15\textsuperscript{th} Global Forum on Tourism Statistics},
  Year                     = {2016},

  Address                  = {Cusco, Peru},
  Number                   = {from},

  File                     = {:Nur16a - Ossi Nurmi.pdf:PDF}
}

@InProceedings{NatRomLeo08b,
  Title                    = {Overcome Selection Bias in Web Surveys. An Application of Propensity Score Method When Target Differs From General Population},
  Author                   = {Michela Natilli and Maria Francesca Romano and Laura Leone},
  Booktitle                = {Societa Italiana di Statistica},
  Year                     = {2008},

  File                     = {:NatRomLeo08b - Michela Natilli and Maria Francesca Romano and Laura Leone.pdf:PDF},
  Keywords                 = {web survey, selection bias, propensity score}
}

@InProceedings{NatRomLeo08a,
  Title                    = {An Application of Propensity Score Method to overcome Selection Bias in Web Surveys},
  Author                   = {Michela Natilli and Maria Francesca Romano and Laura Leone},
  Booktitle                = {VII Wapor Seminar on Quality Criteria in Survey Research},
  Year                     = {2008},

  File                     = {:NatRomLeo08a - Michela Natilli and Maria Francesca Romano and Laura Leone.pdf:PDF},
  Keywords                 = {web survey, special population, bias, propensity score},
  Url                      = {http://hdl.handle.net/11382/300295}
}

@InProceedings{DeNStaLarSebQueLep16a,
  Title                    = {The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective},
  Author                   = {Marco De Nadai and Jacopo Staiano and Roberto Larcher and Nicu Sebe and Daniele Quercia and Bruno Lepri},
  Booktitle                = {Proceedings of the 25\textsuperscript{th} International Conference on World Wide Web - {WWW} {\textquotesingle}16},
  Year                     = {2016},
  Publisher                = {{ACM} Press},

  Abstract                 = {A fundamental research question that urban planners,
The Death and Life of Great American Cities was written sociologists and economists are investigating is what creates},
  Doi                      = {10.1145/2872427.2883084},
  File                     = {:DeNStaLarSebQueLep16a - Marco De Nadai and Jacopo Staiano and Roberto Larcher and Nicu Sebe and Daniele Quercia and Bruno Lepri.pdf:PDF}
}

@PhdThesis{Nab09a,
  Title                    = {Adaptive, Reliable, and Accurate Positioning Model for Location-Based and Services},
  Author                   = {Mohammad Mousa Al Nabhan},
  School                   = {School of Engineering and Design, Brunel University},
  Year                     = {2009},

  File                     = {:Nab09a - Mohammad Mousa Al Nabhan.pdf:PDF}
}

@Article{Mul01a,
  author    = {Keith E. Muller},
  title     = {Computing the confluent hypergeometric function, M ( a,b,x )},
  journal   = {Numerische Mathematik},
  year      = {2001},
  volume    = {90},
  number    = {1},
  pages     = {179--196},
  month     = nov,
  doi       = {10.1007/s002110100285},
  publisher = {Springer Nature},
}

@InProceedings{MosGum17a,
  Title                    = {Examining the applicability of Location Based Services to determine the movement patterns of commuters between Sandton and Park station in Johannesburg city},
  Author                   = {Mangakane Retsebile Moswane and Trynos Gumbo},
  Booktitle                = {Conference proceedings},
  Year                     = {2017},

  Abstract                 = {The movement of people within cities forms patterns and changes the development of transport systems as well as innovations within the Information and Communication Technologies (ICT) sector. The City of Johannesburg has been witnessing massive transformations in urban public transport systems in the past decade and very little is currently known about the movement patterns of commuters between major centres of the city. Investigating and illuminating novel insights on the movement patterns of commuters is very imperative and essential given the multiplicity of modes and centres in increasing decentralized cities such as the Johannesburg Metropolitan City. This work therefore examine the applicability of location based services to determine the movement patterns of Gautrain and Rea Vaya commuters between Sandton and Park station centres, using a case study research design and mixed methods approaches consisting of qualitative, quantitative and spatial data. This research presents novel data analysed into empirical results suggesting that location based services plays a pivotal influence in determining movement of urban public transport commuters in Johannesburg city. The findings also reveal the complexity of spatial and communicative platforms in multiplicity of urban public modes resulting in complex models of movement patterns. These empirical results require further research on the applicability of location based services in determining movement patterns of commuters, with the aim of corroborating the prospects of agglomerating an urban mobility model at a city wide scale.},
  File                     = {:MosGum17a - Mangakane Retsebile Moswane and Trynos Gumbo.pdf:PDF},
  Keywords                 = {micro city centres, movement patterns, Johannesburg metropoitan city, urban public transport, South Africa},
  Url                      = {http://hdl.handle.net/10210/244381}
}

@Misc{Moo06a,
  Title                    = {Cellular Phone Triangulation and Trilateration},

  Author                   = {Robert D. Moody},
  Year                     = {2006},

  File                     = {:Moo06a - Robert D. Moody.pdf:PDF}
}

@Article{deMHidVerBlo13a,
  author    = {Yves-Alexandre de Montjoye and C{\'{e}}sar A. Hidalgo and Michel Verleysen and Vincent D. Blondel},
  title     = {Unique in the Crowd: The privacy bounds of human mobility},
  journal   = {Scientific Reports},
  year      = {2013},
  volume    = {3},
  number    = {1},
  month     = mar,
  doi       = {10.1038/srep01376},
  file      = {:deMHidVerBlo13a - Unique in the Crowd_ the Privacy Bounds of Human Mobility.pdf:PDF},
  publisher = {Springer Nature},
}

@Article{MohEdwMcC08a,
  author    = {Marian Mohr and Christopher Edwards and Ben McCarthy},
  title     = {A study of {LBS} accuracy in the {UK} and a novel approach to inferring the positioning technology employed},
  journal   = {Computer Communications},
  year      = {2008},
  volume    = {31},
  number    = {6},
  pages     = {1148--1159},
  month     = apr,
  doi       = {10.1016/j.comcom.2008.01.039},
  publisher = {Elsevier {BV}},
}

@Article{MohMolNas11a,
  author    = {Moein Mohammadi and Ehsan Molaei and Ali Naserasadi},
  title     = {A Survey on Location based Services and Positioning Techniques},
  journal   = {International Journal of Computer Applications},
  year      = {2011},
  volume    = {24},
  number    = {5},
  pages     = {1--5},
  month     = jun,
  doi       = {10.5120/2946-3928},
  publisher = {Foundation of Computer Science},
}

@InProceedings{SchOttFri10a,
  Title                    = {J. Schlaich and T. Otterstatter and M. Friedrich},
  Author                   = {Generating Trajectories from Mobile and Phone Data},
  Booktitle                = {TRB 89\textsuperscript{th} Annual Meeting},
  Year                     = {2010},

  Address                  = {Washington DC, USA},
  Month                    = jan,

  File                     = {:SchOttFri10a - Generating Trajectories from Mobile and Phone Data.pdf:PDF}
}

@InCollection{MirDeh09a,
  author    = {Hamid Mirebrahim and Mehdi Dehghan},
  title     = {Monte Carlo Localization of Mobile Sensor Networks Using the Position Information of Neighbor Nodes},
  booktitle = {Ad-Hoc, Mobile and Wireless Networks},
  publisher = {Springer Berlin Heidelberg},
  year      = {2009},
  editor    = {P.M. Ruiz and J.J. Garcia-Luna-Aceves},
  volume    = {5793},
  series    = {LNCS},
  pages     = {270--283},
  abstract  = {Localization is a fundamental problem in wireless sensor networks.
Most existing localization algorithm is designed for static sensor networks. 
There are a few localization methods for mobile sensor networks. However, 
Sequential Monte Carlo method (SMC) has been used in localization of mobile 
sensor networks recently. In this paper, we propose a localization algorithm 
based on SMC which can improve the location accuracy. A new method is used 
for sample generation. In that, samples distributes uniformly over the area from 
which samples are drawn instead of random generation of samples in that area. 
This can reduces the number of required samples; besides, this new sample 
generation method enables the algorithm to estimate the maximum location 
error of each node more accurately. Our algorithm also uses the location 
estimation of non-anchor neighbor nodes more efficiently than other 
algorithms. This can improve the localization estimation accuracy highly.},
  doi       = {10.1007/978-3-642-04383-3_20},
  keywords  = {Mobile sensor network, Localization, Sequential Monte Carlo method},
}

@Article{Mil17a,
  author    = {Peter V. Miller},
  title     = {Is There a Future for Surveys?},
  journal   = {Public Opinion Quarterly},
  year      = {2017},
  volume    = {81},
  number    = {S1},
  pages     = {205--212},
  doi       = {10.1093/poq/nfx008},
  publisher = {Oxford University Press ({OUP})},
}

@Article{MilGoo14a,
  author    = {Harvey J. Miller and Michael F. Goodchild},
  title     = {Data-driven geography},
  journal   = {{GeoJournal}},
  year      = {2014},
  volume    = {80},
  number    = {4},
  pages     = {449--461},
  month     = oct,
  doi       = {10.1007/s10708-014-9602-6},
  publisher = {Springer Nature},
}

@Article{MihAngBulCan11a,
  author    = {Lyudmila Mihaylova and Donka Angelova and David Bull and Nishan Canagarajah},
  title     = {Localization of Mobile Nodes in Wireless Networks with Correlated in Time Measurement Noise},
  journal   = {{IEEE} Transactions on Mobile Computing},
  year      = {2011},
  volume    = {10},
  number    = {1},
  pages     = {44--53},
  month     = jan,
  doi       = {10.1109/tmc.2010.132},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Men18a,
  author    = {Xiao-Li Meng},
  title     = {Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 {US} presidential election},
  journal   = {The Annals of Applied Statistics},
  year      = {2018},
  volume    = {12},
  number    = {2},
  pages     = {685--726},
  month     = jun,
  doi       = {10.1214/18-aoas1161sf},
  publisher = {Institute of Mathematical Statistics},
}

@InProceedings{DeMSeyDebLusDewBaeWirDemReiReu16a,
  author    = {Freddy De Meersman and Gerdy Seynaeve and Marc Debusschere and Patrick Lusyne and Pieter Dewitte and Youri Baeyens and Albrecht Wirthmann and Christophe Demunter and Fernando Reis and Hannes I. Reuter},
  title     = {Assessing the Quality and of Mobile and Phone Data as a Source of Statistics},
  booktitle = {European Conference on Quality in Official Statistics (Q2016)},
  year      = {2016},
  address   = {Madrid},
  month     = jun,
  file      = {:DeMSeyDebLusDewBaeWirDemReiReu16a - Assessing the Quality and of Mobile and Phone Data As a Source of Statistics.pdf:PDF},
  keywords  = {mobile phone data, big data, official statistics, quality, Belgium},
}

@Article{Mau06a,
  author    = {Ueli Maurer},
  title     = {Secure multi-party computation made simple},
  journal   = {Discrete Applied Mathematics},
  year      = {2006},
  volume    = {154},
  number    = {2},
  pages     = {370--381},
  month     = feb,
  doi       = {10.1016/j.dam.2005.03.020},
  publisher = {Elsevier {BV}},
}

@InProceedings{MatFish01a,
  Title                    = {Accuracy of current Mobile Phone Location: Limitations on the New Cellular Geography},
  Author                   = {Mateos P. and Fisher P.F.},
  Booktitle                = {Paper presented at the GIS Research UK 13\textsuperscript{th} Annual Conference (GISRUK)},
  Year                     = {2001},

  Address                  = {University of Glasgow, Glasgow, Scotland},
  Month                    = apr,
  Pages                    = {136},

  File                     = {:MatFish01a - Mateos P. and Fisher P.F..pdf:PDF}
}

@InBook{MatFis06a,
  chapter   = {Spatiotemporal Accuracy in Mobile Phone Location: Assessing the New Cellular Geography},
  pages     = {188--211},
  title     = {Dynamic and Mobile GIS: Investigating Changes in Space and Time},
  publisher = {{CRC} {P}ress},
  year      = {2006},
  author    = {Pablo Mateos and Peter F. Fisher},
  editor    = {Jane Drummond and Roland Billen and Elsa Jo\~{a}o and David Forrest},
  isbn      = {9780849390920},
}

@InProceedings{Mat05a,
  Title                    = {Mapping the space of flows: evaluating mobile phone location as a method to track the mobile society},
  Author                   = {Pablo Mateos},
  Booktitle                = {CUPUM2005 Conference},
  Year                     = {2005},

  Address                  = {London, UK},

  Abstract                 = {This paper evaluates the use of mobile phone location as a methodology to measure the},
  File                     = {:Mat05a - Pablo Mateos.pdf:PDF},
  Keywords                 = {Mobile Phone Location, Spatiotemporal accuracy, Moving object tracking, Time Geography}
}

@Article{MarMilZan11a,
  author    = {Giampiero Marra and David L. Miller and Luca Zanin},
  title     = {Modelling the spatiotemporal distribution of the incidence of resident foreign population},
  journal   = {Statistica Neerlandica},
  year      = {2011},
  volume    = {66},
  number    = {2},
  pages     = {133--160},
  month     = nov,
  doi       = {10.1111/j.1467-9574.2011.00500.x},
  publisher = {Wiley},
}

@Article{MarDesNik08a,
  author    = {J.G. Markoulidakis and C. Dessiniotis and D. Nikolaidis},
  title     = {Part two: Kalman filtering options for error minimization in statistical terminal assisted mobile positioning},
  journal   = {Computer Communications},
  year      = {2008},
  volume    = {31},
  number    = {6},
  pages     = {1138--1147},
  month     = apr,
  doi       = {10.1016/j.comcom.2008.01.029},
  publisher = {Elsevier {BV}},
}

@Book{MaoFid09a,
  Title                    = {Localization Algorithms and Strategies for Wireless Sensor Networks},
  Author                   = {Guoqiang Mao and Bar\i\c{s} Fidan},
  Publisher                = {Information Science Reference},
  Year                     = {2009},

  Address                  = {Hershey-New York},

  File                     = {:Mao et al - 2009 - Localization algorithms and strategies for wireless sensor networks.pdf:PDF},
  ISBN                     = {978-1-60566-396-8}
}

@PhdThesis{Mal18a,
  Title                    = {Bias and beyond in digital trace data},
  Author                   = {Momin M. Malik},
  School                   = {UPMC Center for Machine Learning and Health},
  Year                     = {2018},

  File                     = {:Mal18a - Momin M. Malik.pdf:PDF}
}

@Book{Mal09a,
  Title                    = {RTLS for {D}ummies},
  Author                   = {Ajay Malik},
  Publisher                = {Wiley},
  Year                     = {2009},

  Address                  = {Indianapolis, Indiana (India)},

  File                     = {:Malik - 2009 - RTLS For Dummies.pdf:PDF},
  ISBN                     = {978-0-470-39868-5}
}

@Article{MahIsaZinMahManIsm17a,
  author   = {M.F.M. Mahyuddin and A.A. M.Isa and M.S.I.M Zin and Afifah Maheran A.H and Z. Manap and M.K. Ismail Abstract},
  title    = {Overview of Positioning Techniques for {LTE} Technology},
  journal  = {Journal of Telecommunication, Electronics and Computer Engineering},
  year     = {2017},
  volume   = {9},
  number   = {2-13},
  pages    = {43--50},
  issn     = {2180-1843},
  abstract = {This paper explains about the capabilities of enabling LBS and emergency services on the networks, with
location positioning in wireless broadband communications some help from positioning techniques such as Wi-Fi 
and potential of hybrid positioning which are based on long positioning. Hence, although the price of the setup and 
term evolution (LTE) system. Mobile positioning technology deploy is extremely high, these latest positioning techniques 
has become a widely used in condition such as emergency and provides effective and convenient positioning performance 
also in commercial services. Nowadays, with the presence of},
}

@InProceedings{MaWeiChaXie08a,
  Title                    = {Integrating Map Services and Location-based Services for Geo-Referenced Individual Data Collection},
  Author                   = {Xiujun Ma and Zhongya Wei and Yanwei Chai and Kunqing Xie},
  Booktitle                = {{IGARSS} 2008 - 2008 {IEEE} International Geoscience and Remote Sensing Symposium},
  Year                     = {2008},
  Publisher                = {{IEEE}},

  Abstract                 = {Location based service (LBS), provided by wireless
operators, integrate geographical location and end-user},
  Doi                      = {10.1109/igarss.2008.4780032},
  File                     = {:MaWeiChaXie08a - Xiujun Ma and Zhongya Wei and Yanwei Chai and Kunqing Xie.pdf:PDF}
}

@Article{MaLiYuaBau13a,
  author    = {Jingtao Ma and Huan Li and Fang Yuan and Thomas Bauer},
  title     = {Deriving Operational Origin-Destination Matrices From Large Scale Mobile Phone Data},
  journal   = {International Journal of Transportation Science and Technology},
  year      = {2013},
  volume    = {2},
  number    = {3},
  pages     = {183--204},
  month     = sep,
  abstract  = {A method is presented in this work that integrates both emerging and mature data sources to
estimate the operational travel demand in fine spatial and temporal resolutions. By analyzing
individuals{\textquoteright} mobility patterns revealed from their mobile phones, researchers and practitioners are
now equipped to derive the largest trip samples for a region. Because of its ubiquitous use,
extensive coverage of telecommunication services and high penetration rates, travel demand can
be studied continuously in fine spatial and temporal resolutions. The derived sample or seed trip
matrices are coupled with surveyed commute flow data and prevalent travel demand modeling
techniques to provide estimates of the total regional travel demand in the form of origin-
destination (OD) matrices. The methodology is evaluated in a series of real world transportation
planning studies and proved its potentials in application areas such as dynamic traffic assignment
modeling, integrated corridor management and online traffic simulations.},
  doi       = {10.1260/2046-0430.2.3.183},
  publisher = {Elsevier {BV}},
}

@Article{LuFanZhShaYinZhaYan17a,
  author    = {Shiwei Lu and Zhixiang Fang and Xirui Zhang and Shih-Lung Shaw and Ling Yin and Zhiyuan Zhao and Xiping Yang},
  title     = {Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators},
  journal   = {{ISPRS} International Journal of Geo-Information},
  year      = {2017},
  volume    = {6},
  number    = {1},
  pages     = {7},
  month     = jan,
  doi       = {10.3390/ijgi6010007},
  publisher = {{MDPI} {AG}},
}

@Article{LovBirBalvLe15a,
  author    = {Robin Lovelace and Mark Birkin and Dimitris Ballas and Eveline van Leeuwen},
  title     = {Evaluating the Performance of Iterative Proportional Fitting for Spatial Microsimulation: New Tests for an Established Technique},
  journal   = {Journal of Artificial Societies and Social Simulation},
  year      = {2015},
  volume    = {18},
  number    = {2},
  doi       = {10.18564/jasss.2768},
  keywords  = {Iterative proportional fitting, spatial microsimulation, modelling},
  publisher = {Journal of Artificial Societies and Social Simulation},
  url       = {http://jasss.soc.surrey.ac.uk/18/2/21.html},
}

@Article{LouLenRosPicHerFriMarRamBar14a,
  author    = {Thomas Louail and Maxime Lenormand and Oliva G. Cantu Ros and Miguel Picornell and Ricardo Herranz and Enrique Frias-Martinez and Jos{\'{e}} J. Ramasco and Marc Barthelemy},
  title     = {From mobile phone data to the spatial structure of cities},
  journal   = {Scientific Reports},
  year      = {2014},
  volume    = {4},
  number    = {1},
  month     = jun,
  doi       = {10.1038/srep05276},
  publisher = {Springer Nature},
}

@Article{LopPag10a,
  author    = {Jos{\'{e}} L. L{\'{o}}pez and Pedro J. Pagola},
  title     = {The confluent hypergeometric functions $M(a,b;z)$ and $U(a,b;z)$ for large $b$ and $z$},
  journal   = {Journal of Computational and Applied Mathematics},
  year      = {2010},
  volume    = {233},
  number    = {6},
  pages     = {1570--1576},
  month     = jan,
  doi       = {10.1016/j.cam.2009.02.072},
  file      = {:LopPag10a - The Confluent Hypergeometric Functions $M(a,b\;z)$ and $U(a,b\;z)$ for Large $b$ and $z$.pdf:PDF},
  keywords  = {& Phrases: Asymptotic expansions, Confluent hypergeometric functions},
  publisher = {Elsevier {BV}},
}

@Article{LiuMaDuPeiYiPen18a,
  author    = {Zhang Liu and Ting Ma and Yunyan Du and Tao Pei and Jiawei Yi and Hui Peng},
  title     = {Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records},
  journal   = {Transactions in {GIS}},
  year      = {2018},
  volume    = {22},
  number    = {2},
  pages     = {494--513},
  month     = feb,
  doi       = {10.1111/tgis.12323},
  file      = {:LiuMaDuPeiYiPen18a - Mapping Hourly Dynamics of Urban Population Using Trajectories Reconstructed from Mobile Phone Records.pdf:PDF},
  publisher = {Wiley},
}

@InProceedings{LiuLiKri13a,
  Title                    = {Hibernating Process: Modeling Mobile Calls at Multiple Scales},
  Author                   = {Siyuan Liu and Lei Li and Ramayya Krishnan},
  Booktitle                = {13\textsuperscript{th} IEEE International Conference on Data Mining (ICDM)},
  Year                     = {2013},
  Month                    = dec,
  Publisher                = {IEEE},
  Series                   = {Research Collection School Of Information Systems},

  File                     = {:LiuLiKri13a - Siyuan Liu and Lei Li and Ramayya Krishnan.pdf:PDF},
  Institution              = {Singapore Management University Institutional Knowledge at Singapore Management University},
  Type                     = {techreport},
  Url                      = {http://ink.library.smu.edu.sg/sis_research/3477}
}

@Article{LiuPenWuJiaYu18a,
  author    = {Lingbo Liu and Zhenghong Peng and Hao Wu and Hongzan Jiao and Yang Yu},
  title     = {Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and {LUR}-2SFCAe Method},
  journal   = {Sustainability},
  year      = {2018},
  volume    = {10},
  number    = {7},
  pages     = {2432},
  month     = jul,
  doi       = {10.3390/su10072432},
  publisher = {{MDPI} {AG}},
}

@Article{LiuChaSo09a,
  author    = {Hongqing Liu and F. Chan and Hing Cheung So},
  title     = {Non-Line-of-Sight Mobile Positioning Using Factor Graphs},
  journal   = {{IEEE} Transactions on Vehicular Technology},
  year      = {2009},
  volume    = {58},
  number    = {9},
  pages     = {5279--5283},
  month     = nov,
  doi       = {10.1109/tvt.2009.2029553},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{LiuJanWetCoo13a,
  author    = {Feng Liu and Davy Janssens and Geert Wets and Mario Cools},
  title     = {Annotating mobile phone location data with activity purposes using machine learning algorithms},
  journal   = {Expert Systems with Applications},
  year      = {2013},
  volume    = {40},
  number    = {8},
  pages     = {3299--3311},
  month     = jun,
  doi       = {10.1016/j.eswa.2012.12.100},
  publisher = {Elsevier {BV}},
}

@Article{LiuSheHouRaoLiu14a,
  author    = {Dawei Liu and Bin Sheng and Fen Hou and Weixiong Rao and Hongli Liu},
  title     = {From Wireless Positioning to Mobile Positioning: An Overview of Recent Advances},
  journal   = {{IEEE} Systems Journal},
  year      = {2014},
  volume    = {8},
  number    = {4},
  pages     = {1249--1259},
  month     = dec,
  doi       = {10.1109/jsyst.2013.2295136},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{LiuLin09a,
  author    = {Bo-Chieh Liu and Ken-Huang Lin},
  title     = {{SSSD}-Based Mobile Positioning: On the Accuracy Improvement Issues in Distance and Location Estimations},
  journal   = {{IEEE} Transactions on Vehicular Technology},
  year      = {2009},
  volume    = {58},
  number    = {3},
  pages     = {1245--1254},
  month     = mar,
  doi       = {10.1109/tvt.2008.928902},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{LiuLin08a,
  author    = {Bo-Chieh Liu and Ken-Huang Lin},
  title     = {Wireless Location Uses Geometrical Transformation Method With Single Propagation Delay: Model and Detection Performance},
  journal   = {{IEEE} Transactions on Vehicular Technology},
  year      = {2008},
  volume    = {57},
  number    = {5},
  pages     = {2920--2932},
  month     = sep,
  doi       = {10.1109/tvt.2007.912608},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Lit15a,
  author    = {Roderick J. Little},
  title     = {Calibrated Bayes, an inferential paradigm for official statistics in the era of big data},
  journal   = {Statistical Journal of the IAOS},
  year      = {2015},
  volume    = {31},
  number    = {4},
  pages     = {555--563},
  month     = nov,
  issn      = {1874-7655},
  doi       = {10.3233/SJI-150944},
  publisher = {IOS Press},
}

@Book{LiaLiuCar10a,
  Title                    = {Advanced Markov Chain Monte Carlo Methods},
  Author                   = {Faming Liang and Chuanhai Liu and Raymond J. Carroll},
  Publisher                = {John Wiley {\&} Sons, Ltd},
  Year                     = {2010},
  Month                    = jul,

  Doi                      = {10.1002/9780470669723},
  File                     = {:Liang et al - 2010 - Advanced Markov chain Monte Carlo methods.pdf:PDF}
}

@Article{LiYuGaoWuSonGon18a,
  author    = {Zufen Li and Lei Yu and Yong Gao and Yizheng Wu and Guohua Song and Dapeng Gong},
  title     = {Identifying Temporal and Spatial Characteristics of Residents' Trips from Cellular Signaling Data: Case Study of Beijing},
  journal   = {Transportation Research Record: Journal of the Transportation Research Board},
  year      = {2018},
  volume    = {2672},
  number    = {42},
  pages     = {81--90},
  month     = sep,
  doi       = {10.1177/0361198118793495},
  publisher = {{SAGE} Publications},
}

@Article{LiLiWanVasLaiWan15a,
  author    = {Xiaomin Li and Di Li and Jiafu Wan and Athanasios V. Vasilakos and Chin-Feng Lai and Shiyong Wang},
  title     = {A review of industrial wireless networks in the context of Industry 4.0},
  journal   = {Wireless Networks},
  year      = {2015},
  volume    = {23},
  number    = {1},
  pages     = {23--41},
  month     = nov,
  doi       = {10.1007/s11276-015-1133-7},
  publisher = {Springer Nature},
}

@Article{LiCheDuaYanGuo14a,
  author    = {Weifeng Li and Xiaoyun Cheng and Zhengyu Duan and Dongyuan Yang and Gaohua Guo},
  title     = {A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data},
  journal   = {Computational Intelligence and Neuroscience},
  year      = {2014},
  volume    = {2014},
  pages     = {1--11},
  doi       = {10.1155/2014/363502},
  publisher = {Hindawi Limited},
}

@Article{LiDraCasSesWinColPetJiaHawSteChe16a,
  author    = {Songnian Li and Suzana Dragicevic and Francesc Ant{\'{o}}n Castro and Monika Sester and Stephan Winter and Arzu Coltekin and Christopher Pettit and Bin Jiang and James Haworth and Alfred Stein and Tao Cheng},
  title     = {Geospatial big data handling theory and methods: A review and research challenges},
  journal   = {{ISPRS} Journal of Photogrammetry and Remote Sensing},
  year      = {2016},
  volume    = {115},
  pages     = {119--133},
  month     = may,
  doi       = {10.1016/j.isprsjprs.2015.10.012},
  publisher = {Elsevier {BV}},
}

@Article{LiJiaXieMicTumZhoMan14a,
  author    = {Ming-Xia Li and Zhi-Qiang Jiang and Wen-Jie Xie and Salvatore Miccich{\`{e}} and Michele Tumminello and Wei-Xing Zhou and Rosario N. Mantegna},
  title     = {A comparative analysis of the statistical properties of large mobile phone calling networks},
  journal   = {Scientific Reports},
  year      = {2014},
  volume    = {4},
  number    = {1},
  month     = may,
  doi       = {10.1038/srep05132},
  publisher = {Springer Nature},
}

@Article{LiXuTanWanLi18a,
  author    = {Jingjing Li and Lizhi Xu and Ling Tang and Shouyang Wang and Ling Li},
  title     = {Big data in tourism research: A literature review},
  journal   = {Tourism Management},
  year      = {2018},
  volume    = {68},
  pages     = {301--323},
  month     = oct,
  doi       = {10.1016/j.tourman.2018.03.009},
  publisher = {Elsevier {BV}},
}

@InProceedings{LesEskSarSalRuf18a,
  author    = {Titi Kanti Lestari and Siim Esko and Sarpono and Erki Saluveer and Rifa Rufiadi},
  title     = {Indonesia{\textquoteright}s Experience of using Signaling Mobile Positioning Data for Official Tourism Statistics},
  booktitle = {15\textsuperscript{th} World Forum on Tourism Statistics},
  year      = {2018},
  address   = {Cusco, Peru},
  month     = nov,
  file      = {:LesEskSarSalRuf18a - Indonesia's Experience of Using Signaling Mobile Positioning Data for Official Tourism Statistics.pdf:PDF},
  keywords  = {Big Data, Mobile Positioning Data, Signaling data, CDR, Error},
  url       = {http://www.15th-tourism-stats-forum.com/papers.html},
}

@Article{LeiGel17a,
  author    = {Thomas J. Leininger and Alan E. Gelfand},
  title     = {Bayesian Inference and Model Assessment for Spatial Point Patterns Using Posterior Predictive Samples},
  journal   = {Bayesian Analysis},
  year      = {2017},
  volume    = {12},
  number    = {1},
  pages     = {1--30},
  month     = mar,
  doi       = {10.1214/15-ba985},
  publisher = {Institute of Mathematical Statistics},
}

@InProceedings{LauBloDouGatPerBorEbeAadMie12a,
  Title                    = {The mobile data challenge: Big data for mobile computing research},
  Author                   = {Juha K. Laurila and Jan Blom and Olivier Dousse and Daniel Gatica-P\'{e}rez and Olivier Bornet and Julien Eberle and Imad Aad and Markus Miettinen},
  Booktitle                = {Proceedings of the Workshop on the Nokia Mobile Data Challenge, in Conjunction with the 10\textsuperscript{th} International Conference on Pervasive Computing},
  Year                     = {2012},
  Pages                    = {1--8},

  Abstract                 = {the data generated from sensors and applications are giving
This paper presents an overview of the Mobile Data Chal- rise to a new research domain across computing and social
lenge (MDC), a large-scale research initiative aimed at gen- science. Researchers are beginning to examine issues in be-
erating innovations around smartphone-based research, as havioral and social science from the Big Data perspective --
well as community-based evaluation of related mobile data by using large-scale mobile data as input to characterize and
analysis methodologies. First we review the Lausanne Data understand real-life phenomena, including individual traits,
Collection Campaign (LDCC) -- an initiative to collect unique, as well as human mobility, communication, and interaction
longitudinal smartphone data set for the basis of the MDC. patterns [11, 12, 9].
Then, we introduce the Open and Dedicated Tracks of the
MDC; describe the specific data sets used in each of them; This new research, whose findings are clearly important to
and discuss some of the key aspects in order to generate society at large, has been often conducted within corpora-
privacy-respecting, challenging, and scientifically relevant tions that historically have had access to these data types,
mobile data resources for wider use of the research commu- including telecom operators [13] or Internet companies [6],
nity. The concluding remarks will summarize the paper. or through granted data access to academics in highly re-},
  Doi                      = {10.1130/01092},
  File                     = {:LauBloDouGatPerBorEbeAadMie12a - Juha K. Laurila and Jan Blom and Olivier Dousse and Daniel Gatica-P_'{e}rez and Olivier Bornet and Julien Eberle and Imad Aad and Markus Miettinen.pdf:PDF}
}

@Article{LasDemFriMcLMuk11a,
  author    = {Marek Laskowski and Bryan CP Demianyk and Marcia R Friesen and Robert D McLeod and Shamir N Mukhi},
  title     = {Improving Agent Based Models and Validation through Data Fusion},
  journal   = {Online Journal of Public Health Informatics},
  year      = {2011},
  volume    = {3},
  number    = {2},
  month     = nov,
  doi       = {10.5210/ojphi.v3i2.3607},
  keywords  = {Agent Based Modeling; Personal Contact Patterns},
  publisher = {University of Illinois Libraries},
}

@Article{LaoPanDesMarPajNou08a,
  author    = {C. Laoudias and C.G. Panayiotou and C. Desiniotis and J.G. Markoulidakis and J. Pajunen and S. Nousiainen},
  title     = {Part one: The Statistical Terminal Assisted Mobile Positioning methodology and architecture},
  journal   = {Computer Communications},
  year      = {2008},
  volume    = {31},
  number    = {6},
  pages     = {1126--1137},
  month     = apr,
  doi       = {10.1016/j.comcom.2008.01.052},
  publisher = {Elsevier {BV}},
}

@Misc{Laoxxa,
  author = {Christos Laoudias},
  title  = {$\Pi$3: Overview of location techniques},
  file   = {:Laoxxa - Pi3_ Overview of Location Techniques.pdf:PDF},
  url    = {http://www2.ucy.ac.cy/~laoudias/pages/penek/deliverables/D3.pdf},
}

@Article{LanMilLuPeeChoCam10a,
  author    = {Nicholas Lane and Emiliano Miluzzo and Hong Lu and Daniel Peebles and Tanzeem Choudhury and Andrew Campbell},
  title     = {A survey of mobile phone sensing},
  journal   = {{IEEE} Communications Magazine},
  year      = {2010},
  volume    = {48},
  number    = {9},
  pages     = {140--150},
  month     = sep,
  abstract  = {Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.},
  booktitle = {140},
  doi       = {10.1109/mcom.2010.5560598},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Lan14a,
  Title                    = {Uses of Big Data for Official Statistics: Privacy, Incentives, Statistical Challenges, and Other Issues},
  Author                   = {Steve Landefeld},
  Booktitle                = {Discussion Paper for the International Conference on Big Data for Official Statistics},
  Year                     = {2014},
  Month                    = oct,

  Abstract                 = {This paper provides an overview of big data and their use in producing official statistics. Although advances in information technology, data sources, and methods have driven interest
in the use of "big" sets of business and administrative government data collected and used for non-statistical purposes, use of such data is not new. Nor is it likely to be a panacea for statistical agencies confronting demands for more, better, and faster data with fewer resources. However, with careful attention to incentives, protection of privacy, and integration of these non-statistical data with existing statistical data, big data can play a large role in improving the accuracy, timeliness, and relevance of economic statistics at a lower cost than expanding existing data collections.},
  File                     = {:Lan14a - Steve Landefeld.pdf:PDF}
}

@Article{LamBlodeKHuePriSmoDoo08a,
  author    = {Renaud Lambiotte and Vincent D. Blondel and Cristobald de Kerchove and Etienne Huens and Christophe Prieur and Zbigniew Smoreda and Paul Van Dooren},
  title     = {Geographical dispersal of mobile communication networks},
  journal   = {Physica A: Statistical Mechanics and its Applications},
  year      = {2008},
  volume    = {387},
  number    = {21},
  pages     = {5317--5325},
  month     = sep,
  doi       = {10.1016/j.physa.2008.05.014},
  publisher = {Elsevier {BV}},
}

@Article{LaMdeL08a,
  author    = {Anthony LaMarca and Eyal de Lara},
  title     = {Location Systems: An Introduction to the Technology Behind Location Awareness},
  journal   = {Synthesis Lectures on Mobile and Pervasive Computing},
  year      = {2008},
  volume    = {3},
  number    = {1},
  pages     = {1--122},
  month     = jan,
  doi       = {10.2200/s00115ed1v01y200804mpc004},
  publisher = {Morgan {\&} Claypool Publishers {LLC}},
}

@InBook{LafLiuWas08a,
  chapter   = {Nonparametric Bayesian and Methods},
  year      = {2008},
  author    = {John Lafferty and Han Liu and Larry Wasserman},
  booktitle = {Copyright c 2008--2010 Do Not Distribute},
  file      = {:LafLiuWas08a - Nonparametric Bayesian and Methods.pdf:PDF},
}

@Article{LabMicKup08a,
  author    = {Miguel A. Labrador and Katina Michael and Axel K{\"{u}}pper},
  title     = {Advanced location-based services},
  journal   = {Computer Communications},
  year      = {2008},
  volume    = {31},
  number    = {6},
  pages     = {1053--1054},
  month     = apr,
  doi       = {10.1016/j.comcom.2008.01.033},
  file      = {:LabMicKup08a - Advanced location-based services.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@Book{Kup15a,
  Title                    = {Location-Based Services: Fundamentals and Operation},
  Author                   = {Axel K\"{u}per},
  Publisher                = {Wiley},
  Year                     = {2015},

  Address                  = {Chichester},

  File                     = {:Küpper - 2005 - Location-based Services_ Fundamentals and Applications.pdf:PDF},
  ISBN                     = {978-0-470-09231-6�}
}

@Article{KunGreSobRat14a,
  author    = {Kevin S. Kung and Kael Greco and Stanislav Sobolevsky and Carlo Ratti},
  title     = {Exploring Universal Patterns in Human Home-Work Commuting from Mobile Phone Data},
  journal   = {{PLoS} {ONE}},
  year      = {2014},
  volume    = {9},
  number    = {6},
  pages     = {e96180},
  month     = jun,
  doi       = {10.1371/journal.pone.0096180},
  editor    = {Jos{\'{e}} J. Ramasco},
  publisher = {Public Library of Science ({PLoS})},
}

@InProceedings{KucBle15a,
  Title                    = {Population Empirical Bayes},
  Author                   = {Alp Kucukelbir and David M. Blei},
  Booktitle                = {UAI'15 Proceeding UAI'15 Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence},
  Year                     = {2015},

  Address                  = {Amsterdam, Netherlands},
  Editor                   = {M. Meila and T. Heskes},
  Month                    = jul,
  Note                     = {ISBN: 978-0-9966431-0-8},
  Pages                    = {444--453},

  Abstract                 = {Bayesian predictive inference analyzes a dataset to make predictions about new observations. When a model does not match the data, predictive accuracy suffers. We develop population empirical Bayes (POP-EB), a hierarchical framework that explicitly models the empirical population distribution as part of Bayesian analysis. We introduce a new concept, the latent dataset, as a hierarchical variable and set the empirical population as its prior. This leads to a new predictive density that mitigates model mismatch. We efficiently apply this method to complex models by proposing a stochastic variational inference algorithm, called bumping variational inference (BUMP-VI). We demonstrate improved predictive accuracy over classical Bayesian inference in three models: a linear regression model of health data, a Bayesian mixture model of natural images, and a latent Dirichlet allocation topic model of scientific documents.},
  File                     = {:KucBle15a - Alp Kucukelbir and David M. Blei.pdf:PDF}
}

@InCollection{KruHor06a,
  author    = {John Krumm and Eric Horvitz},
  title     = {Predestination: Inferring Destinations from Partial Trajectories},
  booktitle = {Lecture Notes in Computer Science},
  publisher = {Springer},
  year      = {2006},
  pages     = {243--260},
  address   = {Berlin Heidelberg},
  abstract  = {We describe a method called Predestination that uses a history of a
driver{\textquoteright}s destinations, along with data about driving behaviors, to predict where 
a driver is going as a trip progresses. Driving behaviors include types of desti-
nations, driving efficiency, and trip times. Beyond considering previously vis-
ited destinations, Predestination leverages an open-world modeling methodol-
ogy that considers the likelihood of users visiting previously unobserved loca-
tions based on trends in the data and on the background properties of locations. 
This allows our algorithm to smoothly transition between {\textquotedblleft}out of the box{\textquotedblright} with 
no training data to more fully trained with increasing numbers of observations. 
Multiple components of the analysis are fused via Bayesian inference to pro-
duce a probabilistic map of destinations. Our algorithm was trained and tested 
on hold-out data drawn from a database of GPS driving data gathered from 169 
different subjects who drove 7,335 different trips.},
  doi       = {10.1007/11853565_15},
}

@Article{Kru08a,
  author    = {John Krumm},
  title     = {A survey of computational location privacy},
  journal   = {Personal and Ubiquitous Computing},
  year      = {2008},
  volume    = {13},
  number    = {6},
  pages     = {391--399},
  month     = oct,
  doi       = {10.1007/s00779-008-0212-5},
  publisher = {Springer Nature},
}

@InProceedings{KroPan12a,
  Title                    = {Mobile Positioning as a possible data source for international travel service statistics},
  Author                   = {Jaanus Kroon and Eesti Pank},
  Booktitle                = {UNECE/CES Seminar on New Frontiers for Statistical Data Collection},
  Year                     = {2012},

  Address                  = {Geneva, Switzerland},
  Note                     = {Working Paper No. 6},

  File                     = {:KroPan12a - Jaanus Kroon and Eesti Pank.pdf:PDF}
}

@Article{Kri10a,
  author    = {Jukka M. Krisp},
  title     = {Planning Fire and Rescue Services by Visualizing Mobile Phone Density},
  journal   = {Journal of Urban Technology},
  year      = {2010},
  volume    = {17},
  number    = {1},
  pages     = {61--69},
  month     = apr,
  doi       = {10.1080/10630731003597330},
  publisher = {Informa {UK} Limited},
}

@Article{KokErdGez18a,
  author    = {Furkan Kokdogan and Osman Erdem and Sinan Gezici},
  title     = {Theoretical limits on localization in single input multiple output ({SIMO}) visible light systems},
  journal   = {Digital Signal Processing},
  year      = {2018},
  volume    = {82},
  pages     = {31--42},
  month     = nov,
  doi       = {10.1016/j.dsp.2018.07.017},
  publisher = {Elsevier {BV}},
}

@Unpublished{Klu16a,
  author = {Franziska Kl\"{u}gl},
  title  = {Agent-Based Simulation Engineering},
  note   = {Habilitationsschrift},
}

@Misc{KleVer17a,
  Title                    = {Access to new data sources for statistics},

  Author                   = {Thilo Klein and Stefaan Verhulst},
  Month                    = may,
  Year                     = {2017},

  Doi                      = {10.1787/9a1fa77f-en},
  File                     = {:KleVer17a - Thilo Klein and Stefaan Verhulst.pdf:PDF},
  Publisher                = {Organisation for Economic Co-Operation and Development ({OECD})}
}

@InProceedings{KiuBloDouGat-PerLau10a,
  Title                    = {Towards rich mobile phone datasets: Lausanne data collection campaign},
  Author                   = {Niko Kiukkonen and Jan Blom and Olivier Dousse and Daniel Gatica-Perez and Juha Laurila},
  Booktitle                = {Proc. ACM 7\textsuperscript{th} Int. Conf. on Pervasive Services},
  Year                     = {2010},
  Month                    = jul,

  Abstract                 = {Mobile phones have recently been used to collect accessible to large parts of the general population and to the
large-scale continuous data about human behavior. In a paradigm non-intrusive nature of data collection applications running
known as people centric sensing, users are not only the carriers quietly on the background of the mobile phone.
of sensing devices, but also the sources and consumers of sensed
events. This paper describes a data collection campaign wherein One of the most widely cited people centric sensing activ-
Nokia N95 phones are allocated to a heterogeneous sample of ities is the Reality Mining project [4]. Since the collection of
nearly 170 participants from Lausanne, a mid-tier city in Switzer- the data set in 2002, it has become a popular resource for the
land, to be used over a period of one year. The data collection people centric sensing community, inspiring research related
software runs on the background of the phones in a non-intrusive to, e.g., social network patterns [5], behavioral regularities [6],
manner, yielding data on modalities such as social interaction
and spatial behavior. The main motivations for organizing a and behavioral entropy [7]. While the scientific contributions
new campaign on top of the ones that have been successfully enabled by the data set have undoubtedly been prevalent, wire-
conducted in the past are the following: First, in comparison less technology has progressed since the campaign. New types
to the Reality Mining data, generated in 2004-2005, the present of sensors appear in todays handsets, adding to the richness
data set is expected to provide a richer means to study location of the modalities that can be collected by the experimental
attributes, in particular, because today{\textquoteright}s mobile phones are more
powerful and equipped with more sensors. Second, we aim to phones. The density of wireless networks, especially in urban
recruit a heterogeneous set of participants, comprising family areas, has also increased due to the proliferation of Bluetooth
and leisure related social networks in addition to organizationally enabled devices and WLAN access points; the sensing of
driven ones. This paper provides a methodological description of stationary as well as moving wireless devices yields more data
the project and shows the potential of the resulting data set in now than it did half a decade ago.
terms of illuminating multiple aspects of human behavior. Hence in order to push the possibilities of data analysis},
  File                     = {:KiuBloDouGat-PerLau10a - Niko Kiukkonen and Jan Blom and Olivier Dousse and Daniel Gatica-Perez and Juha Laurila.pdf:PDF}
}

@Article{KitLau14a,
  author    = {Rob Kitchin and Tracey P. Lauriault},
  title     = {Small data in the era of big data},
  journal   = {{GeoJournal}},
  year      = {2014},
  volume    = {80},
  number    = {4},
  pages     = {463--475},
  month     = oct,
  doi       = {10.1007/s10708-014-9601-7},
  publisher = {Springer Nature},
}

@Article{Kit15b,
  author    = {Rob Kitchin},
  title     = {Big Data and Official Statistics: Opportunities, Challenges and Risks},
  journal   = {{SSRN} Electronic Journal},
  year      = {2015},
  doi       = {10.2139/ssrn.2595075},
  publisher = {Elsevier {BV}},
}

@Article{Kit15a,
  author    = {Rob Kitchin},
  title     = {The opportunities, challenges and risks of big data for official statistics},
  journal   = {Statistical Journal of the IAOS},
  year      = {2015},
  volume    = {31},
  number    = {3},
  pages     = {471--481},
  month     = aug,
  issn      = {1874-7655},
  doi       = {10.3233/SJI-150906},
  publisher = {IOS Press},
}

@Article{Kit13a,
  author    = {Rob Kitchin},
  title     = {Big data and human geography},
  journal   = {Dialogues in Human Geography},
  year      = {2013},
  volume    = {3},
  number    = {3},
  pages     = {262--267},
  month     = nov,
  doi       = {10.1177/2043820613513388},
  publisher = {{SAGE} Publications},
}

@Article{KinRosTan99a,
  author    = {Gary King and Ori Rosen and Martin A. Tanner},
  title     = {Binomial-Beta Hierarchical Models for Ecological Inference},
  journal   = {Sociological Methods {\&} Research},
  year      = {1999},
  volume    = {28},
  number    = {1},
  pages     = {61--90},
  month     = aug,
  doi       = {10.1177/0049124199028001004},
  publisher = {{SAGE} Publications},
}

@Book{Kin97a,
  title     = {A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data},
  publisher = {Princeton University Press},
  year      = {1997},
  author    = {Gary King},
  file      = {:Kin97a - A Solution to the Ecological Inference Problem_ Reconstructing Individual Behavior from Aggregate Data.pdf:PDF;:King - 1997 - Errata_A Solution to the Ecological Inference Problem_ Reconstructing Individual Behavior from Aggregate Data.pdf:PDF},
}

@Article{KimRao11a,
  author    = {J. K. Kim and J. N. K. Rao},
  title     = {Combining data from two independent surveys: a model-assisted approach},
  journal   = {Biometrika},
  year      = {2011},
  volume    = {99},
  number    = {1},
  pages     = {85--100},
  month     = dec,
  doi       = {10.1093/biomet/asr063},
  publisher = {Oxford University Press ({OUP})},
}

@Article{KhoGauFioYac18a,
  author    = {Ghazaleh Khodabandelou and Vincent Gauthier and Marco Fiore and Mounim A. El Yacoubi},
  title     = {Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata},
  journal   = {{IEEE} Transactions on Mobile Computing},
  year      = {2018},
  pages     = {1--1},
  abstract  = {Communication-enabled devices routinely carried by individuals have become pervasive, opening unprecedented
opportunities for collecting digital metadata about the mobility of large populations. In this paper, we propose a novel methodology for
the estimation of people density at metropolitan scales, using subscriber presence metadata collected by a mobile operator. Our
approach suits the estimation of static population densities, i.e., of the distribution of dwelling units per urban area contained in
traditional censuses. More importantly, it enables the estimation of dynamic population densities, i.e., the time-varying distributions of
people in a conurbation. By leveraging substantial real-world mobile network metadata and ground-truth information, we demonstrate
that the accuracy of our solution is superior to that granted by state-of-the-art methods in practical heterogeneous urban scenarios.},
  doi       = {10.1109/tmc.2018.2871156},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{Ker11a,
  author    = {Jouni Kerman},
  title     = {Neutral noninformative and informative conjugate beta and gamma prior distributions},
  journal   = {Electronic Journal of Statistics},
  year      = {2011},
  volume    = {5},
  number    = {0},
  pages     = {1450--1470},
  doi       = {10.1214/11-ejs648},
  publisher = {Institute of Mathematical Statistics},
}

@Article{KelVilChr17a,
  author    = {Csaba Kelen and Pablo Vilarino and Georgios Christou},
  title     = {Advanced demand data collection technologies for multi modal strategic modelling},
  journal   = {Transportation Research Procedia},
  year      = {2017},
  volume    = {27},
  pages     = {1058--1065},
  doi       = {10.1016/j.trpro.2017.12.074},
  publisher = {Elsevier {BV}},
}

@TechReport{OKe17a,
  Title                    = {Finding Location and with Time and of and Arrival and Time and Difference of and Arrival Techniques},
  Author                   = {Brian O\textquoteunique Keefe},
  Institution              = {Dept. Electrical and Computer Engineering, Tufts University},
  Year                     = {2017},
  Note                     = {ECE Senior Capstone Project 2017 Tech Notes Indoor Navigation for the Visually Impaired},

  File                     = {:OKe17a - Brian O_textquoteunique Keefe.pdf:PDF}
}

@Article{KazGez19a,
  author    = {Ertan Kazikli and Sinan Gezici},
  title     = {Hybrid {TDOA}/{RSS} based localization for visible light systems},
  journal   = {Digital Signal Processing},
  year      = {2019},
  volume    = {86},
  pages     = {19--28},
  month     = mar,
  doi       = {10.1016/j.dsp.2018.12.001},
  publisher = {Elsevier {BV}},
}

@Article{KauKumGup17a,
  author    = {Amanpreet Kaur and Padam Kumar and Govind P. Gupta},
  title     = {A weighted centroid localization algorithm for randomly deployed wireless sensor networks},
  journal   = {Journal of King Saud University - Computer and Information Sciences},
  year      = {2017},
  month     = feb,
  doi       = {10.1016/j.jksuci.2017.01.007},
  publisher = {Elsevier {BV}},
}

@Article{Kar12a,
  author    = {Alan F. Karr},
  title     = {Discussion on statistical use of administrative data: old and new challenges},
  journal   = {Statistica Neerlandica},
  year      = {2012},
  volume    = {66},
  number    = {1},
  pages     = {80--84},
  month     = jan,
  doi       = {10.1111/j.1467-9574.2011.00510.x},
  publisher = {Wiley},
}

@TechReport{Kap17a,
  Title                    = {Analysis of the most recent modelling techniques for big data with particular attention to Bayesian ones},
  Author                   = {George Kapetanios},
  Institution              = {Eurostat},
  Year                     = {2017},

  File                     = {:Kap17a - George Kapetanios.pdf:PDF}
}

@Article{KanBer16a,
  author    = {Joseph Kang and Kyle Bernstein},
  title     = {On Bayesian Inference with Complex Survey Data},
  journal   = {Biometrics {\&} Biostatistics International Journal},
  year      = {2016},
  volume    = {3},
  number    = {5},
  month     = may,
  doi       = {10.15406/bbij.2016.03.00076},
  publisher = {{MedCrave} Group, {LLC}},
}

@Article{KamPit16a,
  author    = {Andreas Kamilaris and Andreas Pitsillides},
  title     = {Mobile Phone Computing and the Internet of Things: A Survey},
  journal   = {{IEEE} Internet of Things Journal},
  year      = {2016},
  volume    = {3},
  number    = {6},
  pages     = {885--898},
  month     = dec,
  doi       = {10.1109/jiot.2016.2600569},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{KamAasSel17a,
  author    = {Pilleriine Kamenjuk and Anto Aasa and Jaanus Sellin},
  title     = {Mapping changes of residence with passive mobile positioning data: the case of {E}stonia},
  journal   = {International Journal of Geographical Information Science},
  year      = {2017},
  volume    = {31},
  number    = {7},
  pages     = {1425--1447},
  month     = mar,
  doi       = {10.1080/13658816.2017.1295308},
  publisher = {Informa {UK} Limited},
}

@TechReport{Joh16a,
  Title                    = {Computing hypergeometric functions rigorously},
  Author                   = {Fredrik Johansson},
  Institution              = {INRIA},
  Year                     = {2016},
  Month                    = jul,
  Type                     = {resreport},

  File                     = {:Joh16a - Fredrik Johansson.pdf:PDF},
  Url                      = {https://hal.inria.fr/hal-01336266v2/document}
}

@InProceedings{JimSecPriRoa05a,
  Title                    = {Tecnolog\'{\i}as sensoriales de localizaci\'{o}n para entornos inteligentes},
  Author                   = {A. Jim\'{e}nez and F. Seco and J. Prieto and J. Roa},
  Booktitle                = {I Congreso Espa\~{n}ol de Inform\'{a}tica. Simposium UCAmI 05 {{\c{C}}}omputaci{\'{o}}n Ubicua e Inteligencia Ambiental},
  Year                     = {2005},

  Address                  = {Granada, Spain},
  Month                    = sep,
  Note                     = {ISBN: 84-9732-442-0},
  Pages                    = {75--86},

  File                     = {:JimSecPriRoa05a - A. Jim_'{e}nez and F. Seco and J. Prieto and J. Roa.pdf:PDF},
  Url                      = {http://www.car.upm-csic.es/lopsi/static/publicaciones/Congreso%20Nacional/ARJimenez_SurveyLocalizacionCUbicua_CEDI_UCAmI_2005.pdf}
}

@Article{JiePenZhiYonYinZhe18a,
  author    = {Gu Jiefan and Xu Peng and Pang Zhihong and Chen Yongbao and Ji Ying and Chen Zhe},
  title     = {Extracting typical occupancy data of different buildings from mobile positioning data},
  journal   = {Energy and Buildings},
  year      = {2018},
  volume    = {180},
  pages     = {135--145},
  month     = dec,
  doi       = {10.1016/j.enbuild.2018.09.002},
  publisher = {Elsevier {BV}},
}

@Article{JiaXieLiPodZhoSta13a,
  author    = {Z.-Q. Jiang and W.-J. Xie and M.-X. Li and B. Podobnik and W.-X. Zhou and H. E. Stanley},
  title     = {Calling patterns in human communication dynamics},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {2013},
  volume    = {110},
  number    = {5},
  pages     = {1600--1605},
  month     = jan,
  doi       = {10.1073/pnas.1220433110},
  publisher = {Proceedings of the National Academy of Sciences},
}

@InProceedings{JiaFioYanFerFraGon13a,
  Title                    = {A review of urban computing for mobile phone traces},
  Author                   = {Shan Jiang and Gaston A. Fiore and Yingxiang Yang and Joseph Ferreira and Emilio Frazzoli and Marta C. Gonz{\'{a}}lez},
  Booktitle                = {Proceedings of the 2\textsuperscript{nd} {ACM} {SIGKDD} International Workshop on Urban Computing - {UrbComp} {\textquotesingle}13},
  Year                     = {2013},
  Publisher                = {{ACM} Press},

  Abstract                 = {1. INTRODUCTION
In this work, we present three classes of methods to extrac- The emergent field of Urban Computing seeks to develop},
  Doi                      = {10.1145/2505821.2505828},
  File                     = {:JiaFioYanFerFraGon13a - Shan Jiang and Gaston A. Fiore and Yingxiang Yang and Joseph Ferreira and Emilio Frazzoli and Marta C. Gonz{_'{a}}lez.pdf:PDF},
  Keywords                 = {ogy with reproducible phenomena that appear in the natural sciences. Basic and common mechanisms are responsible for}
}

@Article{JiaFerGon17a,
  author    = {Shan Jiang and Joseph Ferreira and Marta C. Gonz\'{a}lez},
  title     = {Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore},
  journal   = {{IEEE} Transactions on Big Data},
  year      = {2017},
  volume    = {3},
  number    = {2},
  pages     = {208--219},
  month     = jun,
  abstract  = {In this study, with Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data, which contains},
  doi       = {10.1109/tbdata.2016.2631141},
  file      = {:JiaFerGon17a - Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data A Case Study of Singapore.pdf:PDF},
  keywords  = {call detail record (CDR) data, human mobility networks, mobility motif detection, trajectory data mining},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{JiaYao06a,
  author    = {Bin Jiang and Xiaobai Yao},
  title     = {Location-based services and {GIS} in perspective},
  journal   = {Computers, Environment and Urban Systems},
  year      = {2006},
  volume    = {30},
  number    = {6},
  pages     = {712--725},
  month     = nov,
  doi       = {10.1016/j.compenvurbsys.2006.02.003},
  publisher = {Elsevier {BV}},
}

@Article{JiaJia11a,
  author    = {Bin Jiang and Tao Jia},
  title     = {Agent-based simulation of human movement shaped by the underlying street structure},
  journal   = {International Journal of Geographical Information Science},
  year      = {2011},
  volume    = {25},
  number    = {1},
  pages     = {51--64},
  month     = feb,
  doi       = {10.1080/13658811003712864},
  publisher = {Informa {UK} Limited},
}

@InProceedings{Jia18a,
  Title                    = {Scaling Law and Tobler's Law and for Characterizing and Asymmetries in Geography},
  Author                   = {Bin Jiang},
  Booktitle                = {First European Asymmetry Symposium},
  Year                     = {2018},

  Address                  = {Nice, France},
  Month                    = mar,

  File                     = {:Jia18a - Bin Jiang.pdf:PDF}
}

@InBook{Jay76a,
  chapter   = {Confidence Intervals vs Bayesian Intervals},
  pages     = {175},
  title     = {Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science},
  publisher = {D. Reidel},
  year      = {1976},
  author    = {Jaynes, E. T.},
  editor    = {W. L. Harper and C. A. Hooker},
  address   = {Dordrecht},
}

@Article{JarTenToi17a,
  author    = {Olle J\"{a}rv and Henrikki Tenkanen and Tuuli Toivonen},
  title     = {Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation},
  journal   = {International Journal of Geographical Information Science},
  year      = {2017},
  volume    = {31},
  number    = {8},
  pages     = {1630--1651},
  month     = feb,
  doi       = {10.1080/13658816.2017.1287369},
  file      = {:JarTenToi17a - Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation.pdf:PDF},
  publisher = {Informa {UK} Limited},
}

@TechReport{AAPOR15a,
  Title                    = {AAPOR Report on Big Data},
  Author                   = {Lilli Japec and Frauke Kreuter and Marcus Berg and Paul Biemer and Paul Decker and Cliff Lampe and Julia Lane and Cathy O\textquotesingle Neil and Abe Usher},
  Institution              = {American Association for Public Opinion Research},
  Year                     = {2015},

  File                     = {:AAPOR15a - Lilli Japec and Frauke Kreuter and Marcus Berg and Paul Biemer and Paul Decker and Cliff Lampe and Julia Lane and Cathy O_textquotesingle Neil and Abe Usher.pdf:PDF},
  Url                      = {https://www.aapor.org/Education-Resources/Reports/Big-Data.aspx}
}

@Article{JanValHumRicHla15a,
  author    = {Andreas Janecek and Danilo Valerio and Karin Anna Hummel and Fabio Ricciato and Helmut Hlavacs},
  title     = {The Cellular Network as a Sensor: From Mobile Phone Data to Real-Time Road Traffic Monitoring},
  journal   = {{IEEE} Transactions on Intelligent Transportation Systems},
  year      = {2015},
  volume    = {16},
  number    = {5},
  pages     = {2551--2572},
  month     = oct,
  doi       = {10.1109/tits.2015.2413215},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{IzqMasVel16a,
  Title                    = {Same-day visitors crossing borders a big and data approach using traffic control},
  Author                   = {M. Izquierdo-Valverde and J. Prado-Mascu\~{n}ano and M. Velasco-Gimeno},
  Booktitle                = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  Year                     = {2016},

  Address                  = {Venice, Italy},
  Month                    = nov,

  Abstract                 = {One pilot project recently implemented in INE (Spain) using big data 
is related to the task of building the frame of visitors crossing the 
borders by road. Due to Schengen Area, there is no direct control of 
people crossing the borders with France and Portugal. 
The register of traffic loops provides the number of vehicles for each 
crossing-road, in both ways (going in and out of Spain), per quarter of 
an hour and according to vehicles length. This information is 
completed by the traffic control cameras installed in the border lines. 
The last is a huge database of number plates of vehicles crossing the 
borders. Combining both sets of big registers (responsibility of the 
Traffic Control Directorate), INE builds the population frame to 
estimate the number of foreign vehicles that enter in Spain monthly, 
broken down by nationality. 
An important methodological challenge currently under research is 
the assessment of the potential of the cameras database to estimate 
international same-day visits. 
These estimations are difficult to obtain from traditional outbound 
tourism sample surveys, as international same-day visitors 
concentrate along the borders, while sample design of these surveys 
(with great potential for mirror-statistics) has more general 
objectives, and there is no subsample big enough to characterize 
these trips. Besides, due to the difficulties and high costs of 
conducting surveys at road borders the quality of the estimations of 
inbound same-day trips could be enhanced with this new information. 
Tracking an anonymized number plate through the camera registers 
database is the first step of the analysis. Those databases contain for 
each vehicle the number plate, the frontier point, the nationality of 
the plate and the moment when it is crossing the border. 
Defining a same-day trip in terms of number of hours (less than 24 
and more than 3) between the moment of going out (coming in) Spain 
and the moment of coming back (going back), and extending the 
tracking to detect vehicles that go in and out through different points, 
we can produce estimates of the ratios of same-day trips in respect of 
the total frame numbers. Thus we can derive subtotals to analyze with 
more precision this specific subset of tourism. The first pilot 
experiences presented in the paper produce the inputs for analysis 
and decision making in order to adjust parameters as border points,},
  File                     = {:IzqMasVel16a - M. Izquierdo-Valverde and J. Prado-Mascu_~{n}ano and M. Velasco-Gimeno.pdf:PDF}
}

@InProceedings{IsaBecCacKobRowVar10a,
  Title                    = {A tale of two cities},
  Author                   = {Sibren Isaacman and Richard Becker and Ram{\'{o}}n C{\'{a}}ceres and Stephen Kobourov and James Rowland and Alexander Varshavsky},
  Booktitle                = {Proceedings of the Eleventh Workshop on Mobile Computing Systems {\&} Applications - {HotMobile} {\textquotesingle}10},
  Year                     = {2010},
  Publisher                = {{ACM} Press},

  Abstract                 = {active cell phones in their coverage areas in order to provide},
  Doi                      = {10.1145/1734583.1734589},
  File                     = {:IsaBecCacKobRowVar10a - Sibren Isaacman and Richard Becker and Ram{_'{o}}n C{_'{a}}ceres and Stephen Kobourov and James Rowland and Alexander Varshavsky.pdf:PDF}
}

@InCollection{IsaBecCacKobMarRowVar11a,
  author    = {Sibren Isaacman and Richard Becker and Ram{\'{o}}n C{\'{a}}ceres and Stephen Kobourov and Margaret Martonosi and James Rowland and Alexander Varshavsky},
  title     = {Identifying Important Places in People's Lives from Cellular Network Data},
  booktitle = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  year      = {2011},
  pages     = {133--151},
  abstract  = {People spend most of their time at a few key locations, such as home},
  doi       = {10.1007/978-3-642-21726-5_9},
}

@Article{IqbChoWanCon14a,
  author    = {Md. Shahadat Iqbal and Charisma F. Choudhury and Pu Wang and Marta C. Gonz{\'{a}}lez},
  title     = {Development of origin{\textendash}destination matrices using mobile phone call data},
  journal   = {Transportation Research Part C: Emerging Technologies},
  year      = {2014},
  volume    = {40},
  pages     = {63--74},
  month     = mar,
  doi       = {10.1016/j.trc.2014.01.002},
  file      = {:IqbChoWanCon14a - Development of Origin-Destination Matrices Using Mobile Phone Call Data.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@InCollection{IovOlt-RaiCouSmo13a,
  author    = {Corina Iovan and Ana-Maria Olteanu-Raimond and Thomas Couronn{\'{e}} and Zbigniew Smoreda},
  title     = {Moving and Calling: Mobile Phone Data Quality Measurements and Spatiotemporal Uncertainty in Human Mobility Studies},
  booktitle = {Geographic Information Science at the Heart of Europe},
  publisher = {Springer International Publishing},
  year      = {2013},
  pages     = {247--265},
  doi       = {10.1007/978-3-319-00615-4_14},
}

@Book{Ied15a,
  title     = {Getting Started with OpenBTS{\"{i}}{\textquestiondown}$\sfrac{1}{2}$},
  publisher = {O\textquotesingleReilly Media},
  year      = {2015},
  author    = {Michael Iedema},
  file      = {:Iedema - 2015 - Getting Started with OpenBTS.pdf:PDF},
}

@Article{HuaTan14a,
  author    = {X. Huang and J. Tan},
  title     = {Understanding spatio-temporal mobility patterns for seniors, child/student and adult using smart card data},
  journal   = {{ISPRS} - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  year      = {2014},
  volume    = {{XL}-1},
  pages     = {167--172},
  month     = nov,
  doi       = {10.5194/isprsarchives-xl-1-167-2014},
  publisher = {Copernicus {GmbH}},
}

@InProceedings{HuEva04a,
  Title                    = {Localization for mobile sensor networks},
  Author                   = {Lingxuan Hu and David Evans},
  Booktitle                = {Proceedings of the 10\textsuperscript{th} annual international conference on Mobile computing and networking - {MobiCom} {\textquotesingle}04},
  Year                     = {2004},
  Publisher                = {{ACM} Press},

  Abstract                 = {1. INTRODUCTION},
  Doi                      = {10.1145/1023720.1023726},
  File                     = {:HuEva04a - Lingxuan Hu and David Evans.pdf:PDF},
  Keywords                 = {sensor network applications (for example, sensor nodes dropped from plane over a hostile territory). Hop count}
}

@Article{HowLovTur08a,
  author    = {Mark Howell and Steve Love and Mark Turner},
  title     = {User characteristics and performance with automated mobile phone systems},
  journal   = {International Journal of Mobile Communications},
  year      = {2008},
  volume    = {6},
  number    = {1},
  pages     = {1},
  doi       = {10.1504/ijmc.2008.015994},
  publisher = {Inderscience Publishers},
}

@Misc{HowChe16a,
  Title                    = {Estimating temporary populations -- the power of aggregated mobile device data},

  Author                   = {Andrew Howe and Tricia Chester},
  HowPublished             = {Presented at the 2016 Australian Population Association Conference},
  Month                    = dec,
  Note                     = {Sydney, Australia},
  Year                     = {2016},

  File                     = {:HowChe16a - Andrew Howe and Tricia Chester.pdf:PDF}
}

@Article{HotSecSobRatPuj14a,
  author    = {Sahar Hoteit and Stefano Secci and Stanislav Sobolevsky and Carlo Ratti and Guy Pujolle},
  title     = {Estimating human trajectories and hotspots through mobile phone data},
  journal   = {Computer Networks},
  year      = {2014},
  volume    = {64},
  pages     = {296--307},
  month     = may,
  doi       = {10.1016/j.comnet.2014.02.011},
  publisher = {Elsevier {BV}},
}

@Article{HosCha15a,
  author    = {Jeffrey A. Hostetler and Richard B. Chandler},
  title     = {Improved state-space models for inference about spatial and temporal variation in abundance from count data},
  journal   = {Ecology},
  year      = {2015},
  volume    = {96},
  number    = {6},
  pages     = {1713--1723},
  month     = jun,
  abstract  = {Models of population dynamics are frequently used for purposes such as testing
hypotheses about density dependence and predicting species{\textquoteright} responses to future environ-
mental change or conservation actions. Fitting models of population dynamics to field data is
challenging because most data sets are characterized by observation error, which can inflate
estimates of process variation if ignored. Recently, state-space models have been developed to
deal with this problem by directly modeling both the observation error and the ecological
process of interest. Conventional state-space models, however, have several important
limitations: (1) they assume that random effects are Gaussian distributed, which implies that
abundance can be negative and that false positive observation errors are equally likely as false
negative errors; (2) they do not admit spatial variation in population dynamics; and (3) some
of the parameters of the model are not estimable. We demonstrate how each of these problems
can be resolved using a class of hierarchical models proposed by Dail and Madsen (2011) that
attributes observation error to imperfect detection. We expand this class of models to
accommodate classical growth models (e.g., exponential and Ricker-logistic), zero-inflation,
and random effects. We also present methods for forecasting population size under future
environmental conditions. Implementation of these ideas is possible using either frequentist or
Bayesian methods, as demonstrated by accompanying R and JAGS code. Results of a
simulation study suggest that bias is negligible and coverage nominal in most cases for the
proposed model extensions. An analysis of data from the North American Breeding Bird
Survey highlights how these methods can be readily applied to existing data, but it also
suggests that precision will be low when direct information about detection probability (such
as is collected using distance sampling or replicated counts) is lacking.},
  doi       = {10.1890/14-1487.1},
  publisher = {Wiley},
}

@Article{HorKer15a,
  author    = {Christopher Horn and Roman Kern},
  title     = {Deriving Public Transportation Timetables with Large-Scale Cell Phone Data},
  journal   = {Procedia Computer Science},
  year      = {2015},
  volume    = {52},
  pages     = {67--74},
  doi       = {10.1016/j.procs.2015.05.026},
  publisher = {Elsevier {BV}},
}

@Article{Hol07a,
  author    = {D. Tim Holt},
  title     = {The Official Statistics Olympic Challenge},
  journal   = {The American Statistician},
  year      = {2007},
  volume    = {61},
  number    = {1},
  pages     = {1--8},
  month     = feb,
  doi       = {10.1198/000313007x168173},
  publisher = {Informa {UK} Limited},
}

@Misc{Her07a,
  Title                    = {Location and Position Measurements Presentation for Licentiate course in measurement science and technology},

  Author                   = {Marion Hermersdorf},
  Note                     = {Presentation for Licentiate course in measurement science and technology},
  Year                     = {2007},

  File                     = {:Her07a - Marion Hermersdorf.pdf:PDF}
}

@Article{HepMalCro16a,
  author    = {Alison Heppenstall and Nick Malleson and Andrew Crooks},
  title     = {{\textquotedblleft}Space, the Final Frontier{\textquotedblright}: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?},
  journal   = {Systems},
  year      = {2016},
  volume    = {4},
  number    = {1},
  pages     = {9},
  month     = jan,
  doi       = {10.3390/systems4010009},
  file      = {:HepMalCro16a - Space, the Final Frontier_ How Good Are Agent Based Models at Simulating Individuals and Space in Cities_.pdf:PDF},
  publisher = {{MDPI} {AG}},
}

@Article{HazScoKru04a,
  author    = {M. Hazas and J. Scott and J. Krumm},
  title     = {Location-aware computing comes of age},
  journal   = {Computer},
  year      = {2004},
  volume    = {37},
  number    = {2},
  pages     = {95--97},
  month     = feb,
  doi       = {10.1109/mc.2004.1266301},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{GusGun05a,
  author    = {F. Gustafsson and F. Gunnarsson},
  title     = {Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements},
  journal   = {{IEEE} Signal Processing Magazine},
  year      = {2005},
  volume    = {22},
  number    = {4},
  pages     = {41--53},
  month     = jul,
  doi       = {10.1109/msp.2005.1458284},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{GupShaJin16a,
  author    = {Preeti Gupta and Arun Sharma and Rajni Jindal},
  title     = {Scalable machine-learning algorithms for big data analytics: a comprehensive review},
  journal   = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
  year      = {2016},
  volume    = {6},
  number    = {6},
  pages     = {194--214},
  month     = sep,
  doi       = {10.1002/widm.1194},
  publisher = {Wiley},
}

@TechReport{GSMA17a,
  Title                    = {The state of mobile fata for social good report},
  Author                   = {GSMA},
  Institution              = {GSMA},
  Year                     = {2017},

  File                     = {:GSMA17a - GSMA.pdf:PDF}
}

@InProceedings{GruGru03a,
  Title                    = {Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking},
  Author                   = {Marco Gruteser and Dirk Grunwald},
  Booktitle                = {Proceedings of the 1\textsuperscript{st} international conference on Mobile systems, applications and services - {MobiSys} {\textquotesingle}03},
  Year                     = {2003},
  Publisher                = {{ACM} Press},

  Abstract                 = {for collection and usage of personal information [10].
Advances in sensing and tracking technology enable Complying with these principles generally requires no-},
  Doi                      = {10.1145/1066116.1189037},
  File                     = {:GruGru03a - Marco Gruteser and Dirk Grunwald.pdf:PDF}
}

@Book{GreWeiAnd01a,
  title     = {Global Positioning Systems, Inertial Navigation, and Integration},
  publisher = {John Wiley \& Sons},
  year      = {2001},
  author    = {Mohinder S. Grewal and Lawrence R. Weill and Angus P. Andrews - ./ 0 - ./ 0 {\"{i}}{\textquestiondown}$\sfrac{1}{2}$},
  edition   = {2\textsuperscript{nd}},
  isbn      = {978-0-470-09971-1},
  file      = {:Grewal - 2001 - Global Positioning Systems, Inertial Navigation, and Integration.pdf:PDF},
  url       = {https://www.wiley.com/en-us/Global+Positioning+Systems%2C+Inertial+Navigation%2C+and+Integration%2C+2nd+Edition-p-9780470099711},
}

@Article{GraShe13a,
  author    = {Mark Graham and Taylor Shelton},
  title     = {Geography and the Future of Big Data, Big Data and the Future of Geography},
  journal   = {Dialogues in Human Geography},
  year      = {2013},
  volume    = {3},
  number    = {3},
  pages     = {255--261},
  month     = nov,
  doi       = {10.1177/2043820613513121},
  file      = {:GraShe13a - Geography and the Future of Big Data, Big Data and the Future of Geography.pdf:PDF},
  publisher = {{SAGE} Publications},
}

@TechReport{Gou14a,
  author      = {James Goulding},
  title       = {Best Practices and Methodology for OD Matrix Creation from CDR data},
  institution = {N/LAB, Unviersity of Nottingham},
  year        = {2014},
  url         = {http://www.cs.nott.ac.uk/~pszgss/NLAB-Best-Practices-and-Methodology-of-OD-Creation.pdf},
}

@MastersThesis{GonYan18a,
  Title                    = {El reto Big Data para la estad{\'{i}}stica p{\'{u}}blica: Estado del arte},
  Author                   = {Jes{\'{u}}s Alberto Gonz{\'{a}}lez-Yanes},
  School                   = {Ingenier{\'{i}}a de Sistemas de Decisi{\'{o}}n, Universidad Rey Juan Carlos I de Madrid},
  Year                     = {2018},

  File                     = {:GonYan18a - Jes{_'{u}}s Alberto Gonz{_'{a}}lez-Yanes.pdf:PDF}
}

@Article{GonHidBar08a,
  author    = {Marta C. Gonz{\'{a}}lez and C{\'{e}}sar A. Hidalgo and Albert-L{\'{a}}szl{\'{o}} Barab{\'{a}}si},
  title     = {Understanding individual human mobility patterns},
  journal   = {Nature},
  year      = {2008},
  volume    = {453},
  number    = {7196},
  pages     = {779--782},
  month     = jun,
  doi       = {10.1038/nature06958},
  file      = {:GonHidBar08a - Understanding individual human mobility patterns.pdf:PDF},
  publisher = {Springer Nature},
}

@Misc{Gil16a,
  Title                    = {Testing the use of cell phone data for inbound tourism statistics for France},

  Author                   = {Fran\c{c}ois Gitton},
  HowPublished             = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  Month                    = nov,
  Year                     = {2016},

  File                     = {:Gil16a - Fran_c{c}ois Gitton.pdf:PDF}
}

@Article{GirVacGerBidRat09a,
  author  = {Fabien Girardin and Andrea Vaccari and Alexandre Gerber and Assaf Biderman and Carlo Ratti},
  title   = {Quantifying urban attractiveness from the distribution and density of digital footprints},
  journal = {International Journal of Spatial Data Infrastructures Research},
  year    = {2009},
  volume  = {4},
  pages   = {175--200},
  url     = {http://ijsdir.jrc.ec.europa.eu/index.php/ijsdir/article/view/147},
}

@Article{GirCalFioRatBla08a,
  author    = {Fabien Girardin and Francesco Calabrese and Filippo Dal Fiore and Carlo Ratti and Josep Blat},
  title     = {Digital Footprinting: Uncovering Tourists with User-Generated Content},
  journal   = {{IEEE} Pervasive Computing},
  year      = {2008},
  volume    = {7},
  number    = {4},
  pages     = {36--43},
  month     = oct,
  doi       = {10.1109/mprv.2008.71},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{GicSzo18a,
  author    = {Johanna Giczi and Katalin Sz{\H{o}}ke},
  title     = {Official Statistics and Big Data},
  journal   = {Intersections},
  year      = {2018},
  volume    = {4},
  number    = {1},
  month     = jan,
  doi       = {10.17356/ieejsp.v4i1.408},
  publisher = {Intersections},
}

@InProceedings{GiaNanPinPed07a,
  Title                    = {Trajectory pattern mining},
  Author                   = {Fosca Giannotti and Mirco Nanni and Fabio Pinelli and Dino Pedreschi},
  Booktitle                = {Proceedings of the 13\textsuperscript{th} {ACM} {SIGKDD} international conference on Knowledge discovery and data mining - {KDD} {\textquotesingle}07},
  Year                     = {2007},
  Publisher                = {{ACM} Press},

  Abstract                 = {ons to understand mobility-related phenomena. In the following two trajectory patterns over regions of interest},
  Doi                      = {10.1145/1281192.1281230},
  File                     = {:GiaNanPinPed07a - Fosca Giannotti and Mirco Nanni and Fabio Pinelli and Dino Pedreschi.pdf:PDF},
  Keywords                 = {objects from region to region. In fact, in our approach a trajectory pattern is a sequence of spatial regions that, on}
}

@Article{GhoGezStr16a,
  author    = {Mohammad Reza Gholami and Sinan Gezici and Erik G. Str{\"{o}}m},
  title     = {{TW}-{TOA} based positioning in the presence of clock imperfections},
  journal   = {Digital Signal Processing},
  year      = {2016},
  volume    = {59},
  pages     = {19--30},
  month     = dec,
  doi       = {10.1016/j.dsp.2016.07.023},
  publisher = {Elsevier {BV}},
}

@Article{Gez07a,
  author    = {Sinan Gezici},
  title     = {A Survey on Wireless Position Estimation},
  journal   = {Wireless Personal Communications},
  year      = {2007},
  volume    = {44},
  number    = {3},
  pages     = {263--282},
  month     = oct,
  doi       = {10.1007/s11277-007-9375-z},
  publisher = {Springer Nature},
}

@Article{GelSha12a,
  author    = {Andrew Gelman and Cosma Rohilla Shalizi},
  title     = {Philosophy and the practice of Bayesian statistics},
  journal   = {British Journal of Mathematical and Statistical Psychology},
  year      = {2012},
  volume    = {66},
  number    = {1},
  pages     = {8--38},
  month     = feb,
  doi       = {10.1111/j.2044-8317.2011.02037.x},
  publisher = {Wiley},
}

@Book{GelHil07a,
  Title                    = {Data Analysis Using Regression and Multilevel/Hierarchical Models},
  Author                   = {Andrew Gelman and Jennifer Hill},
  Publisher                = {Cambridge University Press},
  Year                     = {2007},

  File                     = {:Gelman and Hill - 2007 - Data Analysis Using Regression and Multilevel_Hierarchical Models.pdf:PDF},
  ISBN                     = {9780521867061},
  Url                      = {https://www.cambridge.org/es/academic/subjects/statistics-probability/statistical-theory-and-methods/data-analysis-using-regression-and-multilevelhierarchical-models?format=HB&isbn=9780521867061}
}

@Article{Gel01a,
  author    = {A. E. Gelfand},
  title     = {On the change of support problem for spatio-temporal data},
  journal   = {Biostatistics},
  year      = {2001},
  volume    = {2},
  number    = {1},
  pages     = {31--45},
  month     = mar,
  doi       = {10.1093/biostatistics/2.1.31},
  keywords  = {Bayesian methods; Environmental risk analysis; Geographic Information System (GIS); Kriging; Modifiable areal unit problem; Simulation-based model fitting},
  publisher = {Oxford University Press ({OUP})},
}

@Article{GaoLiuWanMa13a,
  author    = {Song Gao and Yu Liu and Yaoli Wang and Xiujun Ma},
  title     = {Discovering Spatial Interaction Communities from Mobile Phone Data},
  journal   = {Transactions in {GIS}},
  year      = {2013},
  volume    = {17},
  number    = {3},
  pages     = {463--481},
  month     = may,
  doi       = {10.1111/tgis.12042},
  publisher = {Wiley},
}

@Article{GanHai15a,
  author    = {Amir Gandomi and Murtaza Haider},
  title     = {Beyond the hype: Big data concepts, methods, and analytics},
  journal   = {International Journal of Information Management},
  year      = {2015},
  volume    = {35},
  number    = {2},
  pages     = {137--144},
  month     = apr,
  doi       = {10.1016/j.ijinfomgt.2014.10.007},
  publisher = {Elsevier {BV}},
}

@Misc{GalSakSmo18a,
  Title                    = {Understanding socio-spatial segregation in French cities with mobile phone data},

  Author                   = {Lino Galiana and Benjamin Sakarovitch and Zbigniew Smoreda},
  HowPublished             = {DGINS18},
  Month                    = oct,
  Year                     = {2018},

  Abstract                 = {This study combines mobile phone data and geocoded fiscal data to shed new light on},
  File                     = {:GalSakSmo18a - Lino Galiana and Benjamin Sakarovitch and Zbigniew Smoreda.pdf:PDF}
}

@Article{GaiQuaRosZig17a,
  author    = {Sabrina Gaito and Christian Quadri and Gian Paolo Rossi and Matteo Zignani},
  title     = {Urban communications and social interactions through the lens of mobile phone data},
  journal   = {Online Social Networks and Media},
  year      = {2017},
  volume    = {1},
  pages     = {70--81},
  month     = jun,
  doi       = {10.1016/j.osnem.2017.04.003},
  publisher = {Elsevier {BV}},
}

@Book{GabFurGiaNanRin15a,
  Title                    = {Use of Mobile Phone Data to Estimate Visitors Mobility Flows},
  Author                   = {Lorenzo Gabrielli and Barbara Furletti and Fosca Giannotti and Mirco Nanni and Salvatore Rinzivillo},
  Editor                   = {Carlos Canal and Akram Idani},
  Publisher                = {Springer International Publishing},
  Year                     = {2015},

  Booktitle                = {Software Engineering and Formal Methods},
  Doi                      = {10.1007/978-3-319-15201-1_14},
  File                     = {:GabFurGiaNanRin15a.pdf:PDF},
  Pages                    = {214--226}
}

@Article{FurFioStaZieSmo17a,
  author    = {Angelo Furno and Marco Fiore and Razvan Stanica and Cezary Ziemlicki and Zbigniew Smoreda},
  title     = {A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas},
  journal   = {{IEEE} Transactions on Mobile Computing},
  year      = {2017},
  volume    = {16},
  number    = {10},
  pages     = {2682--2696},
  month     = oct,
  abstract  = {Urban landscapes present a variety of socio-topological environments that are associated to diverse human activities. As
the latter affect the way individuals connect with each other, a bound exists between the urban tissue and the mobile communication
demand. In this paper, we investigate the heterogeneous patterns emerging in the mobile communication activity recorded within
metropolitan regions. To that end, we introduce an original technique to identify classes of mobile traffic signatures that are distinctive
of different urban fabrics. Our proposed technique outperforms previous approaches when confronted to ground-truth information, and
allows characterizing the mobile demand in greater detail than that attained in the literature to date. We apply our technique to
extensive real-world data collected by major mobile operators in ten cities. Results unveil the diversity of baseline communication
activities across countries, but also evidence the existence of a number of mobile traffic signatures that are common to all studied
areas and specific to particular land uses.},
  doi       = {10.1109/tmc.2016.2637901},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{FraPlaRosLeeSmyHatCheGilSchSelHofGroHenRei16a,
  author    = {Beate Franke and Jean-Fran{\c{c}}ois Plante and Ribana Roscher and En-shiun Annie Lee and Cathal Smyth and Armin Hatefi and Fuqi Chen and Einat Gil and Alexander Schwing and Alessandro Selvitella and Michael M. Hoffman and Roger Grosse and Dieter Hendricks and Nancy Reid},
  title     = {Statistical Inference, Learning and Models in Big Data},
  journal   = {International Statistical Review},
  year      = {2016},
  volume    = {84},
  number    = {3},
  pages     = {371--389},
  month     = jun,
  abstract  = {Theneedfornewmethodstodealwithbigdataisacommonthemeinmostscientificfields,
althoughitsdefinitiontendstovarywiththecontext.Statisticalideasareanessentialpartofthis,
andasapartialresponse,athematicprogramonstatisticalinference,learning,andmodelsinbig
datawasheldin2015inCanada,underthegeneraldirectionoftheCanadianStatisticalSciences
Institute,withmajorfundingfrom,andmostactivitieslocatedat,theFieldsInstituteforResearch
inMathematicalSciences.Thispapergivesanoverviewofthetopicscovered,describing
challengesandstrategiesthatseemcommontomanydifferentareasofapplication,andincluding
someexamplesofapplicationstomakethesechallengesandstrategiesmoreconcrete.},
  doi       = {10.1111/insr.12176},
  keywords  = {Aggregation, computational complexity, dimension reduction, high--dimensional data, streaming data, networks},
  publisher = {Wiley},
}

@Article{Fou13a,
  author    = {Jean-Louis Fouley},
  title     = {The {BUGS} Book: A Practical Introduction to Bayesian Analysis},
  journal   = {{CHANCE}},
  year      = {2013},
  volume    = {26},
  number    = {4},
  pages     = {56--59},
  month     = nov,
  doi       = {10.1080/09332480.2013.868759},
  publisher = {Informa {UK} Limited},
}

@Article{Flo14a,
  author    = {Luciano Floridi},
  title     = {Open Data, Data Protection, and Group Privacy},
  journal   = {Philosophy {\&} Technology},
  year      = {2014},
  volume    = {27},
  number    = {1},
  pages     = {1--3},
  month     = feb,
  doi       = {10.1007/s13347-014-0157-8},
  publisher = {Springer Nature},
}

@Article{FieJohJun99a,
  author    = {S. E. Fienberg and M. S. Johnson and B. W. Junker},
  title     = {Classical multilevel and Bayesian approaches to population size estimation using multiple lists},
  journal   = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  year      = {1999},
  volume    = {162},
  number    = {3},
  pages     = {383--405},
  month     = oct,
  doi       = {10.1111/1467-985x.00143},
  publisher = {Wiley},
}

@Article{Fie11a,
  author    = {Stephen E. Fienberg},
  title     = {Bayesian Models and Methods in Public Policy and Government Settings},
  journal   = {Statistical Science},
  year      = {2011},
  volume    = {26},
  number    = {2},
  pages     = {212--226},
  month     = may,
  doi       = {10.1214/10-sts331},
  file      = {:Fie11a_Han.pdf:PDF;:Fie11a_Kal.pdf:PDF;:Fie11a - Bayesian Models and Methods in Public Policy and Government Settings.pdf:PDF},
  publisher = {Institute of Mathematical Statistics},
}

@InProceedings{FiaPon-LopTor-GonTor-MorDAl17a,
  Title                    = {Call Detail Records for Human Mobility Studies},
  Author                   = {Pierdomenico Fiadino and Victor Ponce-Lopez and Juan Antonio Torrero-Gonzalez and Marc Torrent-Moreno and Alessandro D{\textquotesingle}Alconzo},
  Booktitle                = {Proceedings of the Workshop on Big Data Analytics and Machine Learning for Data Communication Networks - Big-{DAMA} {\textquotesingle}17},
  Year                     = {2017},
  Publisher                = {{ACM} Press},

  Doi                      = {10.1145/3098593.3098601},
  File                     = {:FiaPon-LopTor-GonTor-MorDAl17a - Pierdomenico Fiadino and Victor Ponce-Lopez and Juan Antonio Torrero-Gonzalez and Marc Torrent-Moreno and Alessandro D{_textquotesingle}Alconzo.pdf:PDF}
}

@InProceedings{FerRosMamZam11a,
  Title                    = {Extracting urban patterns from location-based social networks},
  Author                   = {Laura Ferrari and Alberto Rosi and Marco Mamei and Franco Zambonelli},
  Booktitle                = {Proceedings of the 3\textsuperscript{rd} {ACM} {SIGSPATIAL} International Workshop on Location-Based Social Networks - {LBSN} {\textquotesingle}11},
  Year                     = {2011},
  Publisher                = {{ACM} Press},

  Doi                      = {10.1145/2063212.2063226},
  File                     = {:FerRosMamZam11a - Laura Ferrari and Alberto Rosi and Marco Mamei and Franco Zambonelli.pdf:PDF}
}

@Article{FerMamCol12a,
  author    = {Laura Ferrari and Marco Mamei and Massimo Colonna},
  title     = {Discovering events in the city via mobile network analysis},
  journal   = {Journal of Ambient Intelligence and Humanized Computing},
  year      = {2012},
  volume    = {5},
  number    = {3},
  pages     = {265--277},
  month     = nov,
  doi       = {10.1007/s12652-012-0169-0},
  publisher = {Springer Nature},
}

@Misc{FelSunPenLehdeM16a,
  Title                    = {Using Deep Learning to Predict Demographics from Mobile Phone Metadata},

  Author                   = {Felbo, Bjarke and Sunds{\o}y, P{{\aa}}l and Pentland, Alex and Lehmann, Sune and de Montjoye, Yves-Alexandre},
  HowPublished             = {ICLR 2016 workshop},
  Month                    = nov,
  Year                     = {2015},

  File                     = {:FelSunPenLehdeM16a - Felbo, Bjarke and Sunds{_o}y, P{{_aa}}l and Pentland, Alex and Lehmann, Sune and de Montjoye, Yves-Alexandre.pdf:PDF}
}

@Article{FarGat-Per13a,
  author    = {Katayoun Farrahi and Daniel Gatica-Perez},
  title     = {A probabilistic approach to mining mobile phone data sequences},
  journal   = {Personal and Ubiquitous Computing},
  year      = {2013},
  volume    = {18},
  number    = {1},
  pages     = {223--238},
  month     = feb,
  doi       = {10.1007/s00779-013-0640-8},
  publisher = {Springer Nature},
}

@Article{FarGat-Per10a,
  author    = {Katayoun Farrahi and Daniel Gatica-Perez},
  title     = {Probabilistic Mining of Socio-Geographic Routines From Mobile Phone Data},
  journal   = {{IEEE} Journal of Selected Topics in Signal Processing},
  year      = {2010},
  volume    = {4},
  number    = {4},
  pages     = {746--755},
  month     = aug,
  doi       = {10.1109/jstsp.2010.2049513},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InCollection{FarGat-Per08a,
  author    = {Katayoun Farrahi and Daniel Gatica-Perez},
  title     = {Daily Routine Classification from Mobile Phone Data},
  booktitle = {Machine Learning for Multimodal Interaction},
  publisher = {Springer},
  year      = {2008},
  editor    = {Popescu-Belis, A. and Stiefelhagen, R.},
  volume    = {5237},
  series    = {Lecture Notes in Computer Science},
  pages     = {173--184},
  address   = {Berlin Heidelberg},
  isbn      = {978-3-540-85852-2},
  doi       = {10.1007/978-3-540-85853-9_16},
}

@Article{FanHsuKuo11a,
  author    = {Shih-Hau Fang and Ying-Tso Hsu and Wen-Hsing Kuo},
  title     = {Dynamic Fingerprinting Combination for Improved Mobile Localization},
  journal   = {{IEEE} Transactions on Wireless Communications},
  year      = {2011},
  volume    = {10},
  number    = {12},
  pages     = {4018--4022},
  month     = dec,
  doi       = {10.1109/twc.2011.101211.101957},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{FanHanLiu14a,
  author    = {Jianqing Fan and Fang Han and Han Liu},
  title     = {Challenges of Big Data analysis},
  journal   = {National Science Review},
  year      = {2014},
  volume    = {1},
  number    = {2},
  pages     = {293--314},
  month     = feb,
  doi       = {10.1093/nsr/nwt032},
  publisher = {Oxford University Press ({OUP})},
}

@TechReport{EscWes98a,
  Title                    = {Computing {B}ayesian Nonparametric hierarchical models},
  Author                   = {Michael D. Escobar and Mike West},
  Institution              = {Dept. Statistics, Univesity of Toronto},
  Year                     = {1998},
  Month                    = feb,
  Type                     = {techreport},

  File                     = {:EscWes98a - Michael D. Escobar and Mike West.pdf:PDF}
}

@Article{EllLit00a,
  author    = {Michael R. Elliott and Roderick J. A. Little},
  title     = {A Bayesian Approach to Combining Information from a Census, a Coverage Measurement Survey, and Demographic Analysis},
  journal   = {Journal of the American Statistical Association},
  year      = {2000},
  volume    = {95},
  number    = {450},
  pages     = {351--362},
  month     = jun,
  doi       = {10.1080/01621459.2000.10474205},
  publisher = {Informa {UK} Limited},
}

@Article{EliNadSteKroLin16a,
  author    = {Daniel Elias and Friedrich Nadler and Johannes Stehno and Jens Kr{\"{o}}sche and Manuel Lindorfer},
  title     = {{SOMOBIL} {\textendash} Improving Public Transport Planning Through Mobile Phone Data Analysis},
  journal   = {Transportation Research Procedia},
  year      = {2016},
  volume    = {14},
  pages     = {4478--4485},
  doi       = {10.1016/j.trpro.2016.05.370},
  file      = {:EliNadSteKroLin16a - SOMOBIL - Improving Public Transport Planning through Mobile Phone Data Analysis.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@Article{EldMil15a,
  author    = {Bret D. Elderd and Tom E. X. Miller},
  title     = {Quantifying demographic uncertainty: Bayesian methods for Integral Projection Models ({IPMs})},
  journal   = {Ecological Monographs},
  year      = {2015},
  month     = oct,
  doi       = {10.1890/15-1526.1},
  publisher = {Wiley},
}

@TechReport{Efr13b,
  author      = {Bradley Efron},
  title       = {Empirical Bayes modeling, computation, and accuracy},
  institution = {Stanford University},
  year        = {2013},
  number      = {examples.},
  file        = {:Efr13b - Empirical Bayes modeling, computation, and accuracy.pdf:PDF},
  keywords    = {f -modeling, g-modeling, Bayes rule in terms of f , prior exponential families},
  url         = {http://statweb.stanford.edu/~ckirby/brad/papers/2013EBModeling.pdf},
}

@Article{Efr13a,
  author    = {Bradley Efron},
  title     = {Estimation and Accuracy After Model Selection},
  journal   = {Journal of the American Statistical Association},
  year      = {2013},
  volume    = {109},
  number    = {507},
  pages     = {991--1007},
  month     = jul,
  doi       = {10.1080/01621459.2013.823775},
  publisher = {Informa {UK} Limited},
}

@Book{Efr12a,
  Title                    = {Large-Scale Inference},
  Author                   = {Bradley Efron},
  Publisher                = {Cambridge University Press},
  Year                     = {2012},

  File                     = {:Efron - 2010 - Large-Scale Inference_ Empirical Bayes Methods for Estimation, Testing, and Prediction.pdf:PDF},
  ISBN                     = {9781107619678},
  Url                      = {https://www.cambridge.org/es/academic/subjects/statistics-probability/statistical-theory-and-methods/large-scale-inference-empirical-bayes-methods-estimation-testing-and-prediction?format=PB&isbn=9781107619678}
}

@Article{Efr86a,
  author    = {B. Efron},
  title     = {Why Isn{\textquotesingle}t Everyone a Bayesian?},
  journal   = {The American Statistician},
  year      = {1986},
  volume    = {40},
  number    = {1},
  pages     = {1--5},
  month     = feb,
  doi       = {10.1080/00031305.1986.10475342},
  file      = {:Efr86a - Why Isnt Everyone a Bayesian.pdf:PDF},
  publisher = {Informa {UK} Limited},
}

@TechReport{EdiMcN18a,
  author      = {Gerard Eding and Joe McNeill},
  title       = {Result of the 2017 CMFB Big Data Survey and recommendations for future work},
  institution = {Committee on Momentary, Financial and Balance of Payment Statistics},
  year        = {2018},
  type        = {techreport},
  address     = {Frankfurt am Main 8Germany)},
  month       = feb,
  note        = {55\textsuperscript{th} Meeting},
}

@Article{EagPenLaz09a,
  author    = {N. Eagle and A. Pentland and D. Lazer},
  title     = {Inferring friendship network structure by using mobile phone data},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {2009},
  volume    = {106},
  number    = {36},
  pages     = {15274--15278},
  month     = aug,
  doi       = {10.1073/pnas.0900282106},
  publisher = {Proceedings of the National Academy of Sciences},
}

@Book{DyeBay99a,
  Title                    = {Mobile Positioning},
  Author                   = {M. Dye and Frank Baylin},
  Publisher                = {Mobile Lifestreams Ltd},
  Year                     = {2001},

  File                     = {:DyeBay99a.pdf:PDF}
}

@InProceedings{Dut96a,
  Title                    = {Encoding and Handling Geospatial Data with Hierarchical Triangular Meshes},
  Author                   = {Geoffrey Dutton},
  Booktitle                = {In Proceedings of the 7\textsuperscript{th} Symposium on Spatial Data Handling},
  Year                     = {1996},
  Pages                    = {505--518},

  File                     = {:Dut96a - Geoffrey Dutton.pdf:PDF}
}

@Proceedings{DutMia09a,
  Title                    = {The Global Information Technology Report 2008-2009: Mobility in a Networked World},
  Year                     = {2009},

  Address                  = {Geneva (Switzerland)},
  Editor                   = {Soumitra Dutta and Irene Mia},
  Publisher                = {World Economic Forum and INSEAD},

  Author                   = {Soumitra Dutta and Irene Mia},
  Booktitle                = {The Global Information Technology Report 2008--2009},
  File                     = {:DutMia09a - Soumitra Dutta and Irene Mia.pdf:PDF},
  ISBN                     = {978-92-95044-19-7}
}

@Article{DuaHonMa14a,
  author    = {Rong Duan and Olivia Hong and Guangqin Ma},
  title     = {Semi-Supervised Learning in Inferring Mobile Device Locations},
  journal   = {Quality and Reliability Engineering International},
  year      = {2014},
  volume    = {30},
  number    = {6},
  pages     = {857--866},
  month     = sep,
  doi       = {10.1002/qre.1701},
  publisher = {Wiley},
}

@Article{DuYanLiu17a,
  author   = {Zhanwei Du and Bo Yang and Jiming Liu},
  title    = {Understanding the Spatial and Temporal Activity Patterns of Subway Mobility Flows},
  journal  = {CoRR},
  year     = {2017},
  abstract = {In urban transportation systems, mobility flows in the subway system reflect the spatial and temporal dynamics of working days. To investigate the variability of mobility flows, we analyse the spatial community through a series of snapshots of subway stations over sequential periods. Using Shanghai as a case study, we find that the spatial community snapshots reveal dynamic passenger activities. Adopting a dual-perspective, we apply spatial and temporal models separately to explore where and when individuals travel for entertainment. In the two models, microblog topics and spatial facilities such as food venues and entertainment businesses are used to characterise the spatial popularity of each station and people{\textquoteright}s travelling perceptions. In the studied case, the city centre is characterised by greater social influence, and it is better described by the spatial model. In the temporal model, shorter travel distances motivate individuals to start their trips earlier. Interestingly, as the number of food-related facilities near the starting station increases, until it exceeds 1563, the speed of people{\textquoteright}s journeys slows down. This study provides a method for modelling the effects of social features on mobility flows and for predicting the spatial-temporal mobility flows of newly built subway stations.},
  url      = {https://arxiv.org/pdf/1702.02456.pdf},
}

@Article{DroJagPitSto17a,
  author    = {Marina Drosou and H.V. Jagadish and Evaggelia Pitoura and Julia Stoyanovich},
  title     = {Diversity in Big Data: A Review},
  journal   = {Big Data},
  year      = {2017},
  volume    = {5},
  number    = {2},
  pages     = {73--84},
  month     = jun,
  doi       = {10.1089/big.2016.0054},
  publisher = {Mary Ann Liebert Inc},
}

@InCollection{DoyFarMcLMcCHun07a,
  author    = {John Doyle and Ronan Farrell and Sean McLoone and Tim McCarthy and Peter Hung},
  title     = {Extracting Localised Mobile Activity Patterns from Cumulative Mobile Spectrum RSSI},
  booktitle = {CIICT 2009 : proceedings of the China-Ireland information and communications technologies conference},
  publisher = {National University of Ireland, Dept. of Computer Science},
  year      = {2007},
  editor    = {National University of Ireland},
  pages     = {75--82},
  address   = {Maynooth, Ireland},
  month     = aug,
  isbn      = {9780901519672},
  note      = {Research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/ll168) by Science Foundation Ireland under the National Development Plan and by the Irish research Council for Science, Engineering and Technology under their Embark Initiative in partnership with ESRI Ireland. The authors gratefully acknowledge this support.},
  abstract  = {Techniques for observing the flow of people are invoke certain social issues with regards to privacy [7], [8].
creating new means for observing the dynamics between people As stated in Doyle er al. [9], the mobile phone usage statistic 
and the environments they pass through. This ubiquitous con- commonly employed in mobile usage mapping applications 
nectivity can be observed and interpreted in real-time, through 
mobile device activity patterns. Recent research into urban is a measure of network bandwidth used. Qpically, this is},
  url       = {http://eprints.maynoothuniversity.ie/2536/},
}

@Article{DouMeyRamRidSon15a,
  author    = {Rex W Douglass and David A Meyer and Megha Ram and David Rideout and Dongjin Song},
  title     = {High resolution population estimates from telecommunications data},
  journal   = {{EPJ} Data Science},
  year      = {2015},
  volume    = {4},
  number    = {1},
  month     = may,
  doi       = {10.1140/epjds/s13688-015-0040-6},
  publisher = {Springer Nature},
}

@Article{DobWilEag15a,
  author    = {Adrian Dobra and Nathalie E. Williams and Nathan Eagle},
  title     = {Spatiotemporal Detection of Unusual Human Population Behavior Using Mobile Phone Data},
  journal   = {{PLOS} {ONE}},
  year      = {2015},
  volume    = {10},
  number    = {3},
  pages     = {e0120449},
  month     = mar,
  doi       = {10.1371/journal.pone.0120449},
  editor    = {Boris Podobnik},
  publisher = {Public Library of Science ({PLoS})},
}

@TechReport{DiaoZhuFerRat15a,
  Title                    = {Inferring Individual Daily Activities from Mobile Phone Traces: A {B}oston Example},
  Author                   = {Mi Diao and Yi Zhu and Joseph Ferreira Jr. and Carlo Ratti},
  Institution              = {National University of Singapore/Institute of Real Estate Studies},
  Year                     = {2015},
  Type                     = {resreport},

  File                     = {:DiaoZhuFerRat15a - Mi Diao and Yi Zhu and Joseph Ferreira Jr. and Carlo Ratti.pdf:PDF}
}

@Article{Dha16a,
  author    = {Vasant Dhar},
  title     = {The Future of Artificial Intelligence},
  journal   = {Big Data},
  year      = {2016},
  volume    = {4},
  number    = {1},
  pages     = {5--9},
  month     = mar,
  doi       = {10.1089/big.2016.29004.vda},
  publisher = {Mary Ann Liebert Inc},
}

@Article{Der13a,
  author    = {Jan Derezi{\'{n}}ski},
  title     = {Hypergeometric Type Functions and Their Symmetries},
  journal   = {Annales Henri Poincar{\'{e}}},
  year      = {2013},
  volume    = {15},
  number    = {8},
  pages     = {1569--1653},
  month     = sep,
  doi       = {10.1007/s00023-013-0282-4},
  file      = {:Der13a - Hypergeometric Type Functions and Their Symmetries.pdf:PDF},
  publisher = {Springer Nature},
}

@InProceedings{DemAntBenPhiSuk16a,
  Title                    = {Inferring origin-destination flows using mobile phone data: {A} case study of {S}enegal},
  Author                   = {Merkebe Getachew Demissie and Francisco Antunes and Carlos Bento and Santi Phithakkitnukoon and Titipat Sukhvibul},
  Booktitle                = {2016 13\textsuperscript{th} International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology ({ECTI}-{CON})},
  Year                     = {2016},
  Month                    = jun,
  Publisher                = {{IEEE}},

  Doi                      = {10.1109/ecticon.2016.7561328},
  File                     = {:DemAntBenPhiSuk16a - Merkebe Getachew Demissie and Francisco Antunes and Carlos Bento and Santi Phithakkitnukoon and Titipat Sukhvibul.pdf:PDF}
}

@Article{DemHomCorBen13a,
  author    = {Merkebe Getachew Demissie and Gon{\c{c}}alo Homem de Almeida Correia and Carlos Bento},
  title     = {Exploring cellular network handover information for urban mobility analysis},
  journal   = {Journal of Transport Geography},
  year      = {2013},
  volume    = {31},
  pages     = {164--170},
  month     = jul,
  doi       = {10.1016/j.jtrangeo.2013.06.016},
  file      = {:DemHomCorBen13a - Exploring Cellular Network Handover Information for Urban Mobility Analysis.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@Article{ReyCar2016a,
  author    = {Pilar Rey-del-Castillo and Jes{\'{u}}s Carde{\~{n}}osa},
  title     = {An Exercise in Exploring Big Data for Producing Reliable Statistical Information},
  journal   = {Big Data},
  year      = {2016},
  volume    = {4},
  number    = {2},
  pages     = {120--128},
  month     = jun,
  doi       = {10.1089/big.2015.0045},
  publisher = {Mary Ann Liebert Inc},
}

@InProceedings{DebSonSka16a,
  author    = {Marc Debusschere and Jan Sonck and Michail Skaliotis},
  title     = {Official statistics and mobile network operator partner up in Belgium},
  booktitle = {{OECD} {S}tatistics {N}ewsletter},
  year      = {2016},
  number    = {65},
  pages     = {11--14},
  month     = nov,
  file      = {:DebSonSka16a - Official Statistics and Mobile Network Operator Partner up in Belgium.pdf:PDF},
}

@InProceedings{DebRup07a,
  author    = {Nico Deblauwe and Peter Ruppel},
  title     = {Combining {GPS} and {GSM} Cell-{ID} positioning for Proactive Location-based Services},
  booktitle = {2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking {\&} Services ({MobiQuitous})},
  year      = {2007},
  publisher = {{IEEE}},
  abstract  = {Mobile terminals with built-in GPS receivers are current position of a mobile target, which can be done either
becoming more and more available, thus the public deployment in a terminal-based, terminal-assisted or network-based fash-
of location-based services (LBS) becomes feasible. Upcoming LBS ion. No matter what procedure is chosen, there will always
are no longer only reactive but getting more and more proactive,
enabling the users to subscribe for certain events and get notified remain the problem that positioning consumes power on the
when e.g. a friend approaches or a point of interest comes mobile target (except for the scenarios where electromagnetic
within proximity. However, power consumption for continuous induction is used) and that mobile devices have limited battery
tracking is still a mayor issue with mobile terminals. In this capacity.
paper we define this problem and propose solutions for an energy- For proactive LBSs it is not necessary to have a constant
efficient combination of GPS and GSM Cell-ID positioning for
mobile terminals. We introduce several strategies for extending spatio-temporal accuracy all the time in order to meet the
the lifetime of the battery and show how these strategies can be requirements. E.g. a buddy tracker does not need to know
integrated into existing middleware solutions. Simulations based the exact positions of other users when they are definitely far
on a realistic proactive multi-user context confirm the approach. away. Only if two users approach at an area within they might},
  doi       = {10.1109/mobiq.2007.4450985},
}

@InProceedings{DatRadSab16a,
  Title                    = {How many SIM in your luggage? A strategy to make mobile phone data usable in tourism statistics},
  Author                   = {B. Dattilo and R. Radini and M. Sabato},
  Booktitle                = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  Year                     = {2016},
  Month                    = nov,

  File                     = {:DatRadSab16a - B. Dattilo and R. Radini and M. Sabato.pdf:PDF}
}

@Article{DatBanFinGel16a,
  author    = {Abhirup Datta and Sudipto Banerjee and Andrew O. Finley and Alan E. Gelfand},
  title     = {On nearest-neighbor Gaussian process models for massive spatial data},
  journal   = {Wiley Interdisciplinary Reviews: Computational Statistics},
  year      = {2016},
  volume    = {8},
  number    = {5},
  pages     = {162--171},
  month     = aug,
  doi       = {10.1002/wics.1383},
  publisher = {Wiley},
}

@Article{DaoRizWan02a,
  author    = {Diep Dao and Chris Rizos and Jinling Wang},
  title     = {Location-based services: technical and business issues},
  journal   = {{GPS} Solutions},
  year      = {2002},
  volume    = {6},
  number    = {3},
  pages     = {169--178},
  month     = dec,
  doi       = {10.1007/s10291-002-0031-5},
  publisher = {Springer Nature},
}

@Article{Dan99a,
  author    = {Michael J. Daniels},
  title     = {A prior for the variance in hierarchical models},
  journal   = {Canadian Journal of Statistics},
  year      = {1999},
  volume    = {27},
  number    = {3},
  pages     = {567--578},
  month     = sep,
  abstract  = {The choice of prior distributions for the variances can be important and quite difficult in Bayesian hierar- 
chical and variance component models. For situations where little prior information is available, a {\textquoteright}nonin- 
formative{\textquoteright} type prior is usually chosen. {\textquoteleft}Noninformative{\textquoteright} priors have been discussed by many authors and 
used in many contexts. However, care must be taken using these prior distributions as many are improper 
and thus, can lead to improper posterior distributions. Additionally, in small samples, these priors can be 
{\textquoteright}informative{\textquoteright}. In this paper, we investigate a proper {\textquoteleft}vague{\textquoteright} prior, the uniform shrinkage prior (Strawder- 
man 197 1; Christiansen & Moms 1997). We discuss its properties and show how posterior distributions for 
common hierarchical models using this prior lead to proper posterior distributions. We also illustrate the 
attractive frequentist properties of this prior for a normal hierarchical model including testing and estima- 
tion. To conclude, we generalize this prior to the multivariate situation of a covariance matrix.},
  doi       = {10.2307/3316112},
  publisher = {Wiley},
}

@InProceedings{DaaLoo13a,
  Title                    = {Big {D}ata (and official statistics)},
  Author                   = {Piet Daas and Mark van der Loo},
  Booktitle                = {Meeting on the Management of Statistical Information Systems},
  Year                     = {2013},
  Editor                   = {UNECE/EUROSTAT/OECD/ESCAP},
  Month                    = apr,
  Series                   = {Working Paper},

  File                     = {:DaaLoo13a - Piet Daas and Mark van der Loo.pdf:PDF},
  Url                      = {https://www.unescap.org/sites/default/files/1-Big%20Data%20%28and%20official%20statistics%29-Netherlands.pdf}
}

@Article{CudWilOrmComOrm04a,
  author    = {Gary Cuddeback and Elizabeth Wilson and John G. Orme and Terri Combs-Orme},
  title     = {Detecting and Statistically Correcting Sample Selection Bias},
  journal   = {Journal of Social Service Research},
  year      = {2004},
  volume    = {30},
  number    = {3},
  pages     = {19--33},
  month     = may,
  doi       = {10.1300/j079v30n03_02},
  publisher = {Informa {UK} Limited},
}

@Article{CroCroJenMahAgoSte16a,
  author    = {A.T. Crooks and A. Croitoru and A. Jenkins and R. Mahabir and P. Agouris and A. Stefanidis},
  title     = {User-Generated Big Data and Urban Morphology},
  journal   = {Built Environment},
  year      = {2016},
  volume    = {42},
  number    = {3},
  pages     = {396--414},
  month     = oct,
  doi       = {10.2148/benv.42.3.396},
  publisher = {Alexandrine Press},
}

@Misc{Cra13a,
  Title                    = {The Hidden Biases in Big Data},

  Author                   = {Kate Crawford},
  HowPublished             = {Harvard Business Review},
  Year                     = {2013},

  File                     = {:Cra13a - Kate Crawford.pdf:PDF},
  Url                      = {https://hbr.org/2013/04/the-hidden-biases-in-big-data}
}

@Article{CouSmoRai11a,
  author  = {Thomas Couronn{\'e} and Zbigniew Smoreda and Ana-Maria Olteanu Raimond},
  title   = {Chatty mobiles: individual mobility and communication patterns},
  journal = {CoRR},
  year    = {2011},
  volume  = {abs/1301.6553},
  file    = {:CouSmoRai11a - Chatty mobiles individual mobility and communication patterns.pdf:PDF},
  url     = {https://arxiv.org/ftp/arxiv/papers/1301/1301.6553.pdf},
}

@InProceedings{CouOltSmo11a,
  Title                    = {Urban Mobility: Velocity and Uncertainty in Mobile Phone Data},
  Author                   = {Thomas Couronne and Ana-Maria Olteanu and Zbigniew Smoreda},
  Booktitle                = {2011 {IEEE} Third Int{\textquotesingle}l Conference on Privacy, Security, Risk and Trust and 2011 {IEEE} Third Int{\textquotesingle}l Conference on Social Computing},
  Year                     = {2011},
  Month                    = oct,
  Publisher                = {{IEEE}},

  Doi                      = {10.1109/passat/socialcom.2011.230},
  File                     = {:CouOltSmo11a - Thomas Couronne and Ana-Maria Olteanu and Zbigniew Smoreda.pdf:PDF}
}

@Article{CouKirKorVol13a,
  author    = {Thomas Couronn{\'{e}} and Valery Kirzner and Katerina Korenblat and Zeev Volkovich},
  title     = {Some Features of the Users{\textquotesingle} Activities in the Mobile Telephone Network},
  journal   = {Journal of Pattern Recognition Research},
  year      = {2013},
  volume    = {8},
  number    = {1},
  pages     = {59--65},
  abstract  = {Daily activity of the users of a mobile-phone network is represented as a sequence of input
and output calls and of input and output text messages. Each such sequence corresponds
to its spectrum, the distribution of short two-letter sequences of the same type. It is
shown that the spectra of any user{\textquoteright}s sequences are stable, i.e. reproduced daily. Based
on this, the notion of a user{\textquoteright}s strategy is introduced. The number of different strategies
appears to be limited, in the sense that the number of user groups with the same strategy
is sufficiently small.},
  doi       = {10.13176/11.517},
  file      = {:CouKirKorVol13a - Some Features of the Users Activities in the Mobile Telephone Network.pdf:PDF},
  keywords  = {Mobile phone data, Human behavior learning, Sparsity},
  publisher = {Journal of Pattern Recognition Research},
}

@InProceedings{Cou14a,
  Title                    = {What {B}ig {D}ata may mean for surveys},
  Author                   = {Mick P. Couper},
  Booktitle                = {Proceedings of Statistics Canada Symposium'Beyond traditional survey taking adapting to a changing world '},
  Year                     = {2014},

  File                     = {:Cou14a - Mick P. Couper.pdf:PDF}
}

@Article{Cou13a,
  author   = {Mick P. Couper},
  title    = {Is the Sky and Falling? and New Technology and Changing Media},
  journal  = {Survey Research Methods},
  year     = {2013},
  volume   = {7},
  number   = {3},
  pages    = {145--156},
  issn     = {1864-3361},
  abstract = {In this paper I review three key technology-related trends: 1) big data, 2) non-probability samples, and 3) mobile data collection. I focus on the implications of these trends for survey research and the research profession. With regard to big data, I review a number of concerns
that need to be addressed, and argue for a balanced and careful evaluation of the role that big data can play in the future. I argue that these developments are unlikely to replace transitional survey data collection, but will supplement surveys and expand the range of research methods. I also argue for the need for the survey research profession to adapt to changing circumstances.},
  keywords = {big data; organic data; social media; mobile surveys; non-probability surveys},
}

@Book{Con10a,
  Title                    = {Applied {B}ayesian Hierarchical Methods},
  Author                   = {Peter D. Congdon},
  Publisher                = {{CRC} {P}ress},
  Year                     = {2010},

  Address                  = {Boca Raton},

  File                     = {:Congdon - 2010 - Applied Bayesian Hierarchical Methods.pdf:PDF},
  ISBN                     = {978-1-58488-720-1},
  Url                      = {https://www.crcpress.com/Applied-Bayesian-Hierarchical-Methods/Congdon/p/book/9781584887201}
}

@Article{ComNotAntSar17a,
  author    = {Marco Compagnoni and Roberto Notari and Fabio Antonacci and Augusto Sarti},
  title     = {On the statistical model of source localization based on Range Difference measurements},
  journal   = {Journal of the Franklin Institute},
  year      = {2017},
  volume    = {354},
  number    = {15},
  pages     = {7183--7214},
  month     = oct,
  doi       = {10.1016/j.jfranklin.2017.07.034},
  publisher = {Elsevier {BV}},
}

@Manual{ColLepKir-Jaa10a,
  Title                    = {TKT-2546 Methods for Positioning},
  Author                   = {Jussi Collin and Helena Lepp{\"{a}}koski and Martti Kirkko-Jaakkola},
  Organization             = {Tampere University of Technology},
  Year                     = {2010},

  File                     = {:ColLepKir-Jaa10a - Jussi Collin and Helena Lepp{__{a}}koski and Martti Kirkko-Jaakkola.pdf:PDF},
  Url                      = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.610.2595&rep=rep1&type=pdf}
}

@Article{ColAleAlvMehGon15a,
  author    = {Serdar {\c{C}}olak and Lauren P. Alexander and Bernardo G. Alvim and Shomik R. Mehndiratta and Marta C. Gonz{\'{a}}lez},
  title     = {Analyzing Cell Phone Location Data for Urban Travel},
  journal   = {Transportation Research Record: Journal of the Transportation Research Board},
  year      = {2015},
  volume    = {2526},
  pages     = {126--135},
  month     = jan,
  doi       = {10.3141/2526-14},
  file      = {:ColAleAlvMehGon15a - Analyzing Cell Phone Location Data for Urban Travel.pdf:PDF},
  publisher = {{SAGE} Publications},
}

@Article{ChuSerMarMoe16a,
  author    = {Alvin Chua and Loris Servillo and Ernesto Marcheggiani and Andrew Vande Moere},
  title     = {Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy},
  journal   = {Tourism Management},
  year      = {2016},
  volume    = {57},
  pages     = {295--310},
  month     = dec,
  doi       = {10.1016/j.tourman.2016.06.013},
  publisher = {Elsevier {BV}},
}

@Article{ChrMor97a,
  author    = {Cindy L. Christiansen and Carl N. Morris},
  title     = {Hierarchical Poisson Regression Modeling},
  journal   = {Journal of the American Statistical Association},
  year      = {1997},
  volume    = {92},
  number    = {438},
  pages     = {618--632},
  month     = jun,
  doi       = {10.1080/01621459.1997.10474013},
  publisher = {Informa {UK} Limited},
}

@Misc{ChoDulxxa,
  author = {Driss Choujaa and Naranker Dulay},
  title  = {Activity Recognition from Mobile Phone Data: State of the Art, Prospects and Open Problems},
  year   = {20xx},
  doi    = {ng},
  file   = {:ChoDulxxa - Activity Recognition from Mobile Phone Data_ State of the Art, Prospects and Open Problems.pdf:PDF},
}

@Article{ChiThiTonShiLiu14a,
  author    = {Guanghua Chi and Jean-Claude Thill and Daoqin Tong and Li Shi and Yu Liu},
  title     = {Uncovering regional characteristics from mobile phone data: A network science approach},
  journal   = {Papers in Regional Science},
  year      = {2014},
  volume    = {95},
  number    = {3},
  pages     = {613--631},
  month     = nov,
  doi       = {10.1111/pirs.12149},
  publisher = {Wiley-Blackwell},
}

@Article{Chi09a,
  author    = {Guangqing Chi},
  title     = {Can Knowledge Improve Population Forecasts at Subcounty Levels?},
  journal   = {Demography},
  year      = {2009},
  volume    = {46},
  number    = {2},
  pages     = {405--427},
  doi       = {10.1353/dem.0.0059},
  publisher = {Springer Nature},
}

@Article{CheQin-SheZi-YuHui-Jun13a,
  author  = {Cheng, Zhang and Qing-Sheng, Zhu and Zi-Yu, Chen and Hui-Jun, Liu},
  title   = {Community Mining With Mobile Phone Data},
  journal = {International Information Institute (Tokyo)},
  year    = {2013},
  volume  = {16},
  number  = {6A},
  pages   = {3743--3762},
  month   = jun,
  url     = {https://www.researchgate.net/publication/288444826_Community_mining_with_mobile_phone_data},
}

@Article{CheHuXuGonYanLi18a,
  author    = {Xinguang Chen and Hui Hu and Xiaohui Xu and Jie Gong and Yaqiong Yan and Fang Li},
  title     = {Probability Sampling by Connecting Space with Households Using {GIS}/{GPS} Technologies},
  journal   = {Journal of Survey Statistics and Methodology},
  year      = {2018},
  volume    = {6},
  number    = {2},
  pages     = {149--168},
  month     = jan,
  doi       = {10.1093/jssam/smx032},
  publisher = {Oxford University Press ({OUP})},
}

@Article{CheVen17a,
  author    = {Shu-Heng Chen and Ragupathy Venkatachalam},
  title     = {Agent-based modelling as a foundation for big data},
  journal   = {Journal of Economic Methodology},
  year      = {2017},
  volume    = {24},
  number    = {4},
  pages     = {362--383},
  month     = oct,
  doi       = {10.1080/1350178x.2017.1388964},
  publisher = {Informa {UK} Limited},
}

@InProceedings{CheXieTinAloNagLar17a,
  Title                    = {Data Mining Tourism Patterns},
  Author                   = {Nai Chun Chen and Jenny Xie and Phil Tinn and Luis Alonso and Takehiko Nagakura and Kent Larson},
  Booktitle                = {Protocols, Flows and Glitches, Proceedings of the 22\textsuperscript{nd} International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)},
  Year                     = {2017},

  Address                  = {Hong-Kong},
  Editor                   = {P. Janssen and P. Loh and A. Raonic and M. A. Schnabel},
  Pages                    = {685--695},
  Publisher                = {The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)},

  Abstract                 = {In this study we show how Call Detail Record (CDR) can be
used to better understand the travel patterns of visitors. We show how Origin-Destination (OD) InteractiveMaps can provide transportation information through CDR. We then use aggregation of CDR to show the differences between the travel patterns of visitors from different countries and of different lengths of stay. We also show that visitors move differently during event periods and non-event periods, reflecting the importance of real-time data available by CDR. From CDR, we can gain more detailed and complete information about how tourists move compared to traditional surveys, which can be used to aid smarter transportation systems and urban resource planning.},
  File                     = {:CheXieTinAloNagLar17a - Nai Chun Chen and Jenny Xie and Phil Tinn and Luis Alonso and Takehiko Nagakura and Kent Larson.pdf:PDF},
  Keywords                 = {Machine Learning; Call Detail Record; Original- Destination Matrix; Urban Design Tool}
}

@Article{ChePeiShaLuLiShi18a,
  author    = {Jie Chen and Tao Pei and Shih-Lung Shaw and Feng Lu and Mingxiao Li and Shifen Cheng and Xiliang Liu and Hengcai Zhang},
  title     = {Fine-grained prediction of urban population using mobile phone location data},
  journal   = {International Journal of Geographical Information Science},
  year      = {2018},
  volume    = {32},
  number    = {9},
  pages     = {1770--1786},
  month     = apr,
  doi       = {10.1080/13658816.2018.1460753},
  publisher = {Informa {UK} Limited},
}

@Book{CheGui06a,
  Title                    = {Next Generation Wireless Systems and Networks},
  Author                   = {Hsiao-Hwa Chen and Mohsen Guizani},
  Publisher                = {Wiley},
  Year                     = {2006},

  Address                  = {Chichester},

  File                     = {:Chen and Guizani - 2006 - Next Generation Wireless Systems and Networks.pdf:PDF},
  ISBN                     = {978-0-470-02434-8}
}

@TechReport{CheKot00a,
  Title                    = {A Survey of Context-Aware Mobile Computing Research},
  Author                   = {Guanling Chen and David Kotz},
  Institution              = {Darmouth College},
  Year                     = {2000},

  Address                  = {Hanover, NH, USA},
  Number                   = {TR2000-381},
  Type                     = {techreport},

  Abstract                 = {these devices can be connected without wires:},
  File                     = {:CheKot00a - Guanling Chen and David Kotz.pdf:PDF},
  Publisher                = {IEEE},
  Url                      = {http://www.ncstrl.org:8900/ncstrl/servlet/search?formname=detail\&id=oai%3Ancstrlh%3Adartmouthcs%3Ancstrl.dartmouthcs%2F%2FTR2000-381}
}

@Article{CheBiaMa14a,
  author    = {Cynthia Chen and Ling Bian and Jingtao Ma},
  title     = {From traces to trajectories: How well can we guess activity locations from mobile phone traces?},
  journal   = {Transportation Research Part C: Emerging Technologies},
  year      = {2014},
  volume    = {46},
  pages     = {326--337},
  month     = sep,
  doi       = {10.1016/j.trc.2014.07.001},
  publisher = {Elsevier {BV}},
}

@Article{Chat14a,
  author   = {Subhrajit Chatterjee},
  title    = {A sociological outlook of mobile phone use in society},
  journal  = {International Journal of Interdisciplinary and Multidisciplinary Studies (IJIMS)},
  year     = {2014},
  volume   = {1},
  pages    = {55--63},
  issn     = {2348-0343},
  abstract = {Mobile phones have become the most important and integral part of today{\^{a}}{\texteuro}{{\"{Y}}}s lifestyle and mobile handset has become 
a widely recognized consumer artifact. Where the mobile phones have great and huge merits there are also demerits 
as well. There are also gender differences in mobile phone usage. The primary objective of this article is to show the 
effect of mobile phones on society and this article clearly show that the mobile phone has a huge effect on people 
and the way they interact with others. 
Keywords: Mobile Phone; Object of Communication; Object of Identity, Self-esteem and Symbol; Memory 
Storage; Mobile Phone Surveillance; Role-integrative Functions; Mobile Banking and Mobile Payment; Mobile 
Phone Tracking; Mobile Phone Addiction. 
 
Introduction 
In this Era, mobile phone has become fashionable to everybody since it is very handy; with a mobile phone in our 
hand we can solve many issues and keep most of information around the world. Mobile phones, assist you to the lot 
of business such as, make schedule of working, and keep in touch with their customers. Initially, when they first 
came out mobile phones were only useful for communicating; now they are of multiple uses by them. With the 
arrival of sophisticated mobile phone it can be used for entertainment purposes also. Mobile Phone can be use as an 
effective the leisure time tool to convert human mind from stress level to free level. 
 Although mobile phones are perceived as devices that directly serve the individuals who own them, they are 
also social artifacts. As a communications technology, they support coordination with others. Additionally, mobile 
telephony communicative practice is influenced by the social contexts in which the phones are used. Communicative 
practice is also influenced by attributes of the owners{\^{a}}{\texteuro}{{\"{Y}}} lifestyle, including their social networks. Furthermore, 
because they are devices that are now present in a variety of contexts, and can be remotely and unpredictably 
activated, mobile phones are subject to social scrutiny and play a role in the social world. They are surrounded by a 
system of actors who wittingly or unwittingly play a role in mobile phone conversation. Mobile phones solve 
problems and provide new channels of communication. We can access the entire world's information no matter 
where we are, just by using a device small enough to fit into one hand. Finally, a user{\^{a}}{\texteuro}{{\"{Y}}}s understanding of how 
mobile telephony works is not only a matter of learning about its multiple technical components (hardware, 
software, and network services), but also of understanding service provider policies and integrating information 
garnered from sales, marketing, and billing communications[1]. Mobile telephony is rapidly becoming a feature of 
our culture, yet we do not understand its effects on communicative practice and behavior, especially with respect to 
the interaction and co-evolution of the technology and human activity. As wireless communications proliferate, 
empirical understanding of practice and social impacts of mobile phone becomes relevant for scholars and 
practitioners alike. So exploring the impact of mobile phones on society is the theme of this article. 
 
Concept of Mobile Phone: A mobile phone (also known as a cellular phone, cell phone, and a hand phone) is a 
phone that can make and receive telephone calls over a radio link while moving around a wide geographic area. It 
does so by connecting to a cellular network provided by a mobile phone operator, allowing access to the public 
telephone network. By contrast, a cordless telephone is used only within the short range of a single, private base 
station. In addition to telephony, modern mobile phones also support a wide variety of other services such as text 
messaging, MMS, email, Internet access, short-range wireless communications (infrared, Bluetooth), business 
applications, gaming and photography. Mobile phones that offer these and more general computing capabilities are 
referred to as Smart phones [2]. It can be said that the cultural meaning of the mobile phone has moved beyond that 
of a {\quotedblbase}simple tool{\^{a}}{\texteuro}{{\"{Y}}} or {\quotedblbase}appliance{\^{a}}{\texteuro}{{\"{Y}}}. It has become a commodity. Since virtually everyone owns a mobile phone and 
wears it openly, its value has moved beyond pure utility and into the realm of meaning.},
  url      = {http://www.ijims.com/uploads/7f312a1489818ee30d4fz8.pdf},
}

@Article{CelIn17a,
  author    = {Selek Ceren Celik and Ozlem Durmaz Incel},
  title     = {Semantic place prediction from crowd-sensed mobile phone data},
  journal   = {Journal of Ambient Intelligence and Humanized Computing},
  year      = {2017},
  volume    = {9},
  number    = {6},
  pages     = {2109--2124},
  month     = jul,
  doi       = {10.1007/s12652-017-0549-6},
  publisher = {Springer Nature America, Inc},
}

@Article{CecMamZam15a,
  author    = {Alket Cecaj and Marco Mamei and Franco Zambonelli},
  title     = {Re-identification and information fusion between anonymized {CDR} and social network data},
  journal   = {Journal of Ambient Intelligence and Humanized Computing},
  year      = {2015},
  volume    = {7},
  number    = {1},
  pages     = {83--96},
  month     = jul,
  doi       = {10.1007/s12652-015-0303-x},
  publisher = {Springer Nature},
}

@Misc{ReySkaWirFlorKarRei04a,
  author       = {Pilar Rey Del Castillo and Michail Skaliotis and Albrecht Wirthmann and Denisa Florescu and Martin Karlberg and Fernando Reis},
  title        = {Will {\textquoteleft}big data{\textquoteright} transform official statistics?},
  howpublished = {European Conference on Quality Q2014},
  year         = {2014},
  file         = {:ReySkaWirFlorKarRei04a - Will Big Data Transform Official Statistics.pdf:PDF},
}

@Article{Cas92a,
  author    = {George Casella},
  title     = {Illustrating empirical Bayes methods},
  journal   = {Chemometrics and Intelligent Laboratory Systems},
  year      = {1992},
  volume    = {16},
  number    = {2},
  pages     = {107--125},
  month     = oct,
  doi       = {10.1016/0169-7439(92)80050-E},
  publisher = {Elsevier {BV}},
}

@Manual{Cas88a,
  title        = {Empirical Bayes Methods -- A Tutorial},
  author       = {George Casella},
  organization = {Dept. Statistics. Purdue University},
  year         = {1988},
}

@Article{CarLou00b,
  author    = {Bradley P. Carlin and Thomas A. Louis},
  title     = {Empirical Bayes: Past, Present and Future},
  journal   = {Journal of the American Statistical Association},
  year      = {2000},
  volume    = {95},
  number    = {452},
  pages     = {1286--1289},
  month     = dec,
  doi       = {10.1080/01621459.2000.10474331},
  publisher = {Informa {UK} Limited},
}

@Book{CarLou00a,
  Title                    = {Bayes and Empirical Bayes Methods for Data Analysis},
  Author                   = {Carlin, B. and Louis T.A.},
  Publisher                = {Chapman and Hall/CRC},
  Year                     = {2000},
  Edition                  = {2\textsuperscript{nd}},

  File                     = {:Carlin and Louis - 2000 - Bayes and Empirical Bayes Methods for Data Analysis.pdf:PDF},
  ISBN                     = {9781420057669},
  Url                      = {9781420057669}
}

@Article{CanGonWanSchMadBar08a,
  author    = {Juli{\'{a}}n Candia and Marta C Gonz{\'{a}}lez and Pu Wang and Timothy Schoenharl and Greg Madey and Albert-L{\'{a}}szl{\'{o}} Barab{\'{a}}si},
  title     = {Uncovering individual and collective human dynamics from mobile phone records},
  journal   = {Journal of Physics A: Mathematical and Theoretical},
  year      = {2008},
  volume    = {41},
  number    = {22},
  pages     = {224015},
  month     = may,
  doi       = {10.1088/1751-8113/41/22/224015},
  publisher = {{IOP} Publishing},
}

@Misc{ColTri99a,
  author = {A. Colin Cameron and Pravin K. Trivedi},
  title  = {Essentials of Count Data Regression},
  year   = {1999},
}

@Book{CamTri98a,
  Title                    = {Regression analysis of count data},
  Author                   = {A. Colin Cameron and Pravin K. Trivedi},
  Publisher                = {Cambridge University Press},
  Year                     = {1998},
  Edition                  = {Second},

  File                     = {:Cameron and Trivedi - 1998 - Regression Analysis of Count Data.pdf:PDF;:Cameron and Trivedi - 2013 - Regression Analysis of Count Data - 2nd ed.pdf:PDF},
  ISBN                     = {9781107014169},
  Url                      = {https://www.cambridge.org/es/academic/subjects/economics/econometrics-statistics-and-mathematical-economics/regression-analysis-count-data-2nd-edition?format=HB&isbn=9781107014169}
}

@InCollection{CalYan17a,
  author    = {Mario Callegaro and Yongwei Yang},
  title     = {The Role of Surveys in the Era of {\textquotedblleft}Big Data{\textquotedblright}},
  booktitle = {The Palgrave Handbook of Survey Research},
  publisher = {Springer International Publishing},
  year      = {2017},
  pages     = {175--192},
  month     = oct,
  doi       = {10.1007/978-3-319-54395-6_23},
}

@Article{CalSmoBloRat11a,
  author    = {Francesco Calabrese and Zbigniew Smoreda and Vincent D. Blondel and Carlo Ratti},
  title     = {Interplay between Telecommunications and Face-to-Face Interactions: A Study Using Mobile Phone Data},
  journal   = {{PLoS} {ONE}},
  year      = {2011},
  volume    = {6},
  number    = {7},
  pages     = {e20814},
  month     = jul,
  doi       = {10.1371/journal.pone.0020814},
  editor    = {Enrico Scalas},
  publisher = {Public Library of Science ({PLoS})},
}

@InCollection{CalPerDiLLiuRat10a,
  Title                    = {The Geography of Taste: Analyzing Cell-Phone Mobility and Social Events},
  Author                   = {Francesco Calabrese and Francisco C. Pereira and Giusy Di Lorenzo and Liang Liu and Carlo Ratti},
  Booktitle                = {Lecture Notes in Computer Science},
  Publisher                = {Springer Berlin Heidelberg},
  Year                     = {2010},
  Pages                    = {22--37},

  Doi                      = {10.1007/978-3-642-12654-3_2},
  File                     = {:CalPerDiLLiuRat10a - Francesco Calabrese and Francisco C. Pereira and Giusy Di Lorenzo and Liang Liu and Carlo Ratti.pdf:PDF}
}

@Article{CalDiLLiuRat11a,
  author    = {Francesco Calabrese and Giusy Di Lorenzo and Liang Liu and Carlo Ratti},
  title     = {Estimating Origin-Destination Flows Using Mobile Phone Location Data},
  journal   = {{IEEE} Pervasive Computing},
  year      = {2011},
  volume    = {10},
  number    = {4},
  pages     = {36--44},
  month     = apr,
  booktitle = {Pervasive Computing},
  doi       = {10.1109/mprv.2011.41},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{CalFerBlo14a,
  author    = {Francesco Calabrese and Laura Ferrari and Vincent D. Blondel},
  title     = {Urban Sensing Using Mobile Phone Network Data: A Survey of Research},
  journal   = {{ACM} Computing Surveys},
  year      = {2014},
  volume    = {47},
  number    = {2},
  pages     = {1--20},
  month     = nov,
  doi       = {10.1145/2655691},
  publisher = {Association for Computing Machinery ({ACM})},
}

@Article{CalDiaDiLFerRat13a,
  author    = {Francesco Calabrese and Mi Diao and Giusy Di Lorenzo and Joseph Ferreira and Carlo Ratti},
  title     = {Understanding individual mobility patterns from urban sensing data: A mobile phone trace example},
  journal   = {Transportation Research Part C: Emerging Technologies},
  year      = {2013},
  volume    = {26},
  pages     = {301--313},
  month     = jan,
  doi       = {10.1016/j.trc.2012.09.009},
  publisher = {Elsevier {BV}},
}

@Article{CalColLovParRat11a,
  author    = {Francesco Calabrese and Massimo Colonna and Piero Lovisolo and Dario Parata and Carlo Ratti},
  title     = {Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome},
  journal   = {{IEEE} Transactions on Intelligent Transportation Systems},
  year      = {2011},
  volume    = {12},
  number    = {1},
  pages     = {141--151},
  month     = mar,
  doi       = {10.1109/tits.2010.2074196},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{CafStu98a,
  author    = {J.J. Caffery and G.L. Stuber},
  title     = {Overview of radiolocation in {CDMA} cellular systems},
  journal   = {{IEEE} Communications Magazine},
  year      = {1998},
  volume    = {36},
  number    = {4},
  pages     = {38--45},
  month     = apr,
  abstract  = {Applications for the location of subscribers of wireless servicescontinue to expand. Consequently, location techniques for wire-
less technologies are being investigated. With code-division multiple access (CDMA) being
deployed by a variety of cellular and PCS providers, developing an approach for location in
CDMA networks is imperative. This article discusses the applications of location technolo-
gy, the methods available for its implementation in CDMA networks, and the problems sixth section, sources of error in the
that are encountered when using CDMA networks for positioning. seventh section, and system loading},
  booktitle = {38},
  doi       = {10.1109/35.667411},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{CacRowSmaUrb12a,
  Title                    = {Exploring the Use of Urban Greenspace through Cellular Network Activity},
  Author                   = {Ram{\'{o}}n C{\'{a}}ceres and James Rowland and Christopher Small and Simon Urbanek},
  Booktitle                = {The second workshop on pervasive urban applications (PURBA), in conjunction with Pervasive},
  Year                     = {2012},
  Month                    = jun,

  Abstract                 = {Knowing when and where people use greenspace is key to our
understanding of urban ecology. The number of cellular phones active in
a geographic area can serve as a proxy for human density in that area.
We are using anonymous records of cellular network activity to study
the spatiotemporal patterns of human density in an urban area. This
paper presents the vision and some early results of this effort. First, we
describe our dataset of six months of activity in the New York metropoli-
tan area. Second, we present a novel technique for estimating network
coverage areas. Third, we describe our approach to analyzing changes
in activity volumes within those areas. Finally, we present preliminary
results regarding changes in human density around Central Park. From
winter to summer, we find that density increases in greenspace areas and
decreases in residential areas.},
  File                     = {:CacRowSmaUrb12a - Ram{_'{o}}n C{_'{a}}ceres and James Rowland and Christopher Small and Simon Urbanek.pdf:PDF},
  Url                      = {http://www.kiskeya.net/ramon/work/pubs/purba12.pdf}
}

@Article{CacWidBen07a,
  author    = {N. C\'{a}ceres and J.P. Wideberg and F.G. Ben\' {\i}tez},
  title     = {Deriving origin{\textendash}destination data from a mobile phone network},
  journal   = {{IET} Intelligent Transport Systems},
  year      = {2007},
  volume    = {1},
  number    = {1},
  pages     = {15},
  doi       = {10.1049/iet-its:20060020},
  file      = {:CacWidBen07a - Deriving Origin-Destination Data from a Mobile Phone Network.pdf:PDF},
  publisher = {Institution of Engineering and Technology ({IET})},
}

@Article{BwaChoHess17a,
  author    = {Andrew Bwambale and Charisma F. Choudhury and Stephane Hess},
  title     = {Modelling trip generation using mobile phone data: A latent demographics approach},
  journal   = {Journal of Transport Geography},
  year      = {2017},
  month     = sep,
  doi       = {10.1016/j.jtrangeo.2017.08.020},
  publisher = {Elsevier {BV}},
}

@InCollection{ButZhaDeyGri11a,
  author    = {Senaka Buthpitiya and Ying Zhang and Anind K. Dey and Martin Griss},
  title     = {n-Gram Geo-trace Modeling},
  booktitle = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  year      = {2011},
  pages     = {97--114},
  abstract  = {As location-sensing smart phones and location-based services
gain mainstream popularity, there is increased interest in developing
techniques that can detect anomalous activities. Anomaly detection ca-
pabilities can be used in theft detection, remote elder-care monitoring
systems, and many other applications. In this paper we present an n-
gram based model for modeling a user{\textquoteright}s mobility patterns. Under the
Markovian assumption that a user{\textquoteright}s location at time t depends only on
the last n $-$ 1 locations until t $-$ 1, we can model a user{\textquoteright}s idiosyncratic
location patterns through a collection of n-gram geo-labels, each with
estimated probabilities. We present extensive evaluations of the n-gram
model conducted on real-world data, compare it with the previous ap-
proaches of using T-Patterns and Markovian models, and show that for
anomaly detection the n-gram model outperforms existing work by ap-
proximately 10%. We also show that the model can use a hierarchical
location partitioning system that is able to obscure a user{\textquoteright}s exact loca-
tion, to protect privacy, while still allowing applications to utilize the
obscured location data for modeling anomalies effectively.},
  doi       = {10.1007/978-3-642-21726-5_7},
}

@InProceedings{BudCalCheJes02a,
  Title                    = {A Bayesian method to improve mobile geolocation accuracy},
  Author                   = {Kenneth C. Budka and Doru Calin and Byron Chen and Daniel Jeske},
  Booktitle                = {Proceedings {IEEE} 56\textsuperscript{th} Vehicular Technology Conference},
  Year                     = {2002},
  Number                   = {often},
  Publisher                = {{IEEE}},

  Abstract                 = {We present a geolocation method for GSM/CDMA/UMTS where satisfying the FCC Mandate is not a requirement. It can
networks. A cell area is partitioned into a grid, and a sequential also be used in CDMA systems as will be explained below. To 
Bayesian updating scheme is proposed to identify the grid point 
within the circular belt, defined by the one-way delay between the satisfy the strict requirements of the FCC mandate, A-GPS 
mobile and the base station, that is the most likely position of the enabled handsets are now available in CDMA systems in 
user. Using GSM as case study, we employ an RF simulation model North America and field results have shown superior A-GPS 
to study the accuracy of the algorithm compared to existing methods. performance in open field environments with accuracy in the 
We show that the accuracy of the Bayesian update method is range of 5m-20m. 
relatively insensitive to cell size and robust to parameter settings. 
 The same field trials, however, have shown that the location},
  Doi                      = {10.1109/vetecf.2002.1040757},
  File                     = {:BudCalCheJes02a - Kenneth C. Budka and Doru Calin and Byron Chen and Daniel Jeske.pdf:PDF}
}

@Article{BryGra13a,
  author    = {John R. Bryant and Patrick J. Graham},
  title     = {Bayesian Demographic Accounts: Subnational Population Estimation Using Multiple Data Sources},
  journal   = {Bayesian Analysis},
  year      = {2013},
  volume    = {8},
  number    = {3},
  pages     = {591--622},
  month     = sep,
  doi       = {10.1214/13-ba820},
  publisher = {Institute of Mathematical Statistics},
}

@Article{BryGra15a,
  author    = {John R. Bryant and Patrick Graham},
  title     = {A Bayesian Approach to Population Estimation with Administrative Data},
  journal   = {Journal of Official Statistics},
  year      = {2015},
  volume    = {31},
  number    = {3},
  pages     = {475--487},
  month     = sep,
  doi       = {10.1515/jos-2015-0028},
  publisher = {Walter de Gruyter {GmbH}},
}

@Article{Bro02a,
  author    = {Tyson R. Browning},
  title     = {Process integration using the design structure matrix},
  journal   = {Systems Engineering},
  year      = {2002},
  volume    = {5},
  number    = {3},
  pages     = {180--193},
  doi       = {10.1002/sys.10023},
  publisher = {Wiley},
}

@Manual{BriKroxxa,
  Title                    = {Global System for Mobile Communication (GSM)},
  Author                   = {Pierre Brisson and Peter Kropf},
  Year                     = {20xx},

  File                     = {:BriKroxxa - Pierre Brisson and Peter Kropf.pdf:PDF}
}

@Article{Bri11a,
  author    = {J. M. Brick},
  title     = {The Future of Survey Sampling},
  journal   = {Public Opinion Quarterly},
  year      = {2011},
  volume    = {75},
  number    = {5},
  pages     = {872--888},
  month     = dec,
  doi       = {10.1093/poq/nfr045},
  publisher = {Oxford University Press ({OUP})},
}

@Article{BraHolWik16a,
  author    = {Jonathan R. Bradley and Scott H. Holan and Christopher K. Wikle},
  title     = {Multivariate spatio-temporal survey fusion with application to the American Community Survey and Local Area Unemployment Statistics},
  journal   = {Stat},
  year      = {2016},
  volume    = {5},
  number    = {1},
  pages     = {224--233},
  doi       = {10.1002/sta4.120},
  publisher = {Wiley},
}

@Article{BraZee15a,
  author    = {Barteld Braaksma and Kees Zeelenberg},
  title     = {``Re-make/Re-model{\textquoteright}{\textquoteright}: Should big data change the modelling paradigm in official statistics?},
  journal   = {Statistical Journal of the IAOS},
  year      = {2015},
  volume    = {31},
  number    = {2},
  pages     = {193--202},
  month     = may,
  issn      = {1874-7655},
  doi       = {10.3233/sji-150892},
  file      = {:BraZee15a - Re Make_Re Model_ Should Big Data Change the Modelling Paradigm in Official Statistics_.djvu:Djvu;:BraZee15a - Re Make_Re Model_ Should Big Data Change the Modelling Paradigm in Official Statistics_.pdf:PDF},
  publisher = {IOS Press},
}

@Misc{BoyCra11a,
  Title                    = {Six Provocations and for Big and Data},

  Author                   = {Danah Boyd and Kate Crawford},
  HowPublished             = {Paper to be presented at Oxford Internet Institute{\textquoteright}s {\textquotedblleft}A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society{\textquotedblright}.},
  Month                    = sep,
  Year                     = {2011},

  Booktitle                = {Paper to be presented at Oxford Internet Institute{\textquoteright}s {\textquotedblleft}A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society{\textquotedblright} on September},
  File                     = {:BoyCra11a - Danah Boyd and Kate Crawford.pdf:PDF},
  Url                      = {http://softwarestudies.com/cultural_analytics/Six_Provocations_for_Big_Data.pdf}
}

@TechReport{Boe-SupElsFasKieMcFWin044,
  Title                    = {How to make internet surveys representative: A case study of a two-step weighting procedure},
  Author                   = {Axel B\"{o}rsch-Supan and Detlev Elsner and Heino Fassbender and Rainer Kiefer and Daniel McFadden and Joachim Winter},
  Institution              = {Munich Center for the Economics of Aging at the Max Planck Institute for Social Law and Social Policy},
  Year                     = {2004},
  Note                     = {MEA discussion paper series 04067},

  File                     = {:Boe-SupElsFasKieMcFWin044 - Axel B__{o}rsch-Supan and Detlev Elsner and Heino Fassbender and Rainer Kiefer and Daniel McFadden and Joachim Winter.pdf:PDF},
  Url                      = {http://mea.mpisoc.mpg.de/uploads/user_mea_discussionpapers/loil50ozz320r55b_pd1_040330%20geschuetzt.pdf}
}

@InProceedings{BorNieLem04a,
  Title                    = {Performance of Cell ID+RTT Hybrid Positioning Method for UMTS Radio Networks},
  Author                   = {J. Borkowski and J. Niemela and J. Lempiainen},
  Booktitle                = {Proceedings of European Wireless Conference},
  Year                     = {2004},
  Month                    = feb,
  Pages                    = {487--492},

  File                     = {:BorNieLem04a - J. Borkowski and J. Niemela and J. Lempiainen.pdf:PDF},
  Url                      = {http://research.ac.upc.edu/EW2004/papers/63.pdf}
}

@TechReport{BooBue11a,
  Title                    = {Model-based estimation},
  Author                   = {Harm Jan Boonstra and Bart Buelens},
  Institution              = {Statistics Netherlands},
  Year                     = {2011},

  File                     = {:BooBue11a - Harm Jan Boonstra and Bart Buelens.pdf:PDF}
}

@Article{BonHomOlt-RaiSmo15a,
  author    = {Patrick Bonnel and Etienne Hombourger and Ana-Maria Olteanu-Raimond and Zbigniew Smoreda},
  title     = {Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations},
  journal   = {Transportation Research Procedia},
  year      = {2015},
  volume    = {11},
  pages     = {381--398},
  abstract  = {Mobile phone operators produce enormous amounts of data. In this paper we present applications performed with a dataset
(communication events + handover and Location Area Up-date) collected by the operator Orange from 31 March to 11 April
2009 for the whole Paris Region. Trips are deduced from the spatio-temporal trajectory of devices through a hypothesis of
stationarity within a Location Area in order to define activities. Trips are then aggregated in an origin-destination matrix which is
compared with traditional data (census data and household travel survey).},
  doi       = {10.1016/j.trpro.2015.12.032},
  publisher = {Elsevier {BV}},
}

@Article{Bon02a,
  author    = {Eric Bonabeau},
  title     = {Agent-based modeling Methods and techniques for and simulating human systems},
  journal   = {Proceedings of the National Academy of Sciences},
  year      = {2002},
  volume    = {99},
  number    = {Supplement 3},
  pages     = {7280--7287},
  month     = may,
  abstract  = {Agent-based modeling is a powerful simulation modeling technique
that has seen a number of applications in the last few years,
including applications to real-world business problems. After the
basic principles of agent-based simulation are briefly introduced,
its four areas of application are discussed by using real-world
applications: flow simulation, organizational simulation, market
simulation, and diffusion simulation. For each category, one or
several business applications are described and analyzed.},
  doi       = {10.1073/pnas.082080899},
  publisher = {Proceedings of the National Academy of Sciences},
}

@Article{BoeObedeW17a,
  author    = {Laura Boeschoten and Daniel Oberski and Ton de Waal},
  title     = {Estimating Classification Errors Under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling ({MILC})},
  journal   = {Journal of Official Statistics},
  year      = {2017},
  volume    = {33},
  number    = {4},
  pages     = {921--962},
  month     = dec,
  doi       = {10.1515/jos-2017-0044},
  publisher = {Walter de Gruyter {GmbH}},
}

@Article{Blu12a,
  author    = {Joshua E. Blumenstock},
  title     = {Inferring patterns of internal migration from mobile phone call records: evidence from Rwanda},
  journal   = {Information Technology for Development},
  year      = {2012},
  volume    = {18},
  number    = {2},
  pages     = {107--125},
  month     = feb,
  doi       = {10.1080/02681102.2011.643209},
  publisher = {Informa {UK} Limited},
}

@Article{BloDecKri15a,
  author    = {Vincent D. Blondel and Adeline Decuyper and Gautier Krings},
  title     = {A survey of results on mobile phone datasets analysis},
  journal   = {{EPJ} Data Science},
  year      = {2015},
  volume    = {4},
  number    = {1},
  month     = aug,
  doi       = {10.1140/epjds/s13688-015-0046-0},
  publisher = {Springer Nature},
}

@Article{BloKriTho10a,
  author  = {Vincent Blondel and Gautier Krings and Isabelle Thomas},
  title   = {Regions and borders of mobile telephony in {B}elgium and in the {B}russels metropolitan zone},
  journal = {Brussels Studies: the e-journal for academic research on {B}russels},
  year    = {2010},
  number  = {42},
  pages   = {1--13},
  issn    = {2031-0293},
  url     = {https://perso.uclouvain.be/gautier.krings/docs/EN_129_BruS42EN.pdf},
}

@MastersThesis{Bil17a,
  Title                    = {Data Visualization and of {T}elenor and mobility data},
  Author                   = {Virinchi Billa},
  School                   = {Faculty of Computing. Blekinge Institute of Technology},
  Year                     = {2017},

  File                     = {:Bil17a - Virinchi Billa.pdf:PDF},
  Url                      = {http://www.diva-portal.org/smash/get/diva2:1077156/FULLTEXT02}
}

@Misc{UNGWGBDOF17b,
  Title                    = {Handbook on the use of Mobile Phone data for Official and Statistics},

  Author                   = {UN Global Working Group on Big Data for Official Statistics},
  Year                     = {2017},

  File                     = {:UNGWGBDOF17b - UN Global Working Group on Big Data for Official Statistics.pdf:PDF}
}

@InProceedings{UNGWGBDOF17a,
  Title                    = {Recommendations for Access to proprietary data},
  Author                   = {Global Working Group on Big Data for Official Statistics},
  Booktitle                = {Statistical Commission Background document Forty-eighth session},
  Year                     = {2017},

  File                     = {:UNGWGBDOF17a - Global Working Group on Big Data for Official Statistics.pdf:PDF}
}

@InProceedings{BetCobSch09a,
  Title                    = {Indicators for the Representativeness of Survey Response},
  Author                   = {J. Bethlehem and F. Cobben and B. Schouten},
  Booktitle                = {Statistics Canada{\textquoteright}s International Symposium Series: Proceedings},
  Year                     = {2009},
  Organization             = {Statistics Canada},
  Pages                    = {1--10},
  Series                   = {Component of Statistics Canada Catalogue no. 11-522-X},

  Doi                      = {10.11501.1772},
  File                     = {:BetCobSch09a - J. Bethlehem and F. Cobben and B. Schouten.pdf:PDF}
}

@Article{Bet10a,
  author    = {Jelke Bethlehem},
  title     = {Selection Bias in Web Surveys},
  journal   = {International Statistical Review},
  year      = {2010},
  volume    = {78},
  number    = {2},
  pages     = {161--188},
  month     = jun,
  doi       = {10.1111/j.1751-5823.2010.00112.x},
  publisher = {Wiley},
}

@TechReport{Bet08a,
  Title                    = {How accurate are self-selection web surveys},
  Author                   = {Jelke Bethlehem},
  Institution              = {Statistics Netherlands},
  Year                     = {2008},

  Abstract                 = {A web survey seems to be an attractive means of collecting survey
data, because it provides simple, cheap and fast access to a large group of people. However, there are pitfalls. Due to methodological problems, the quality of the outcomes of web surveys may be seriously affected. This paper addresses one of these problems, and that is self-selection of respondents.
Self-selection leads to a lack of representativity and thus to biased estimates. The effect of self-selection on the distributional characteristics of estimators is described in detail. It is shown that the bias of estimators in self-selection surveys can be much larger than in surveys based on traditional probability samples. A simulation study also shows what can go wrong in a self-selection
web survey. It is explored whether some correction techniques (adjustment weighting and use of reference surveys) can improve the quality of the outcomes. It turns out that there is no guarantee for success.},
  File                     = {:Bet08a - Jelke Bethlehem.pdf:PDF},
  Url                      = {https://www.cbs.nl/nl-nl/achtergrond/2008/39/how-accurate-are-self-selection-web-surveys-}
}

@InProceedings{BerSuh05a,
  Title                    = {Ray Simulations for Evaluating Different Methods Used to Locate Mobiles in Cities},
  Author                   = {Henry L. Bertoni and Jung W. Suh},
  Booktitle                = {Antennas and Propagation Society International Symposium},
  Year                     = {2005},
  Editor                   = {IEEE Press},
  Pages                    = {401--404},
  Publisher                = {IEEE},
  Volume                   = {4B},

  File                     = {:BerSuh05a - Henry L. Bertoni and Jung W. Suh.pdf:PDF}
}

@TechReport{BerLehReidiCKar17a,
  author      = {Maciej Ber{\k{e}}sewicz and Risto Lehtonen and Fernando Reis and Loredana di Consiglio and Martin Karlberg},
  title       = {An overview of methods for treating selectivity in big data sources},
  institution = {Eurostat},
  year        = {2017},
  type        = {Statistical Working Paper},
  abstract    = {Official statistics is now considering seriously big data as a significant data source for producing statistics. It holds the potential for providing faster, cheaper, more detailed and completely new types of statistics. However, the use of big data brings also several challenges. One of them is the nonprobabilistic character of most sources of big data, as very often they were not designed to produce statistics. The resulting selectivity bias is therefore a major concern when using big data. This paper presents a statistical approach to big data, searching for a definition meaningful from the statistical point of view and identifying its main statistical characteristics. It then argues that big data sources share many characteristics with Internet opt-in panel surveys and proposes this as a reference to address selectivity and coverage problems in big data. Coverage and the self-selection process are briefly discussed in mobile network data, Twitter, Google Trends and Wikipedia page views data. An overview of methods which can be used to address selectivity and eliminate, or mitigate, bias is then presented, covering both methods applied at individual level, i.e. at the level of the statistical unit, and at domain level, i.e. at the level of the produced statistics. Finally, the applicability of the methods to the several big data sources is briefly discussed and a framework for adjusting selectivity in big data is proposed.},
  doi         = {10.2785/312232},
}

@Article{Beresewicz2017,
  author    = {Maciej Ber{\k{e}}sewicz},
  title     = {A Two-Step Procedure to Measure Representativeness of Internet Data Sources},
  journal   = {International Statistical Review},
  year      = {2017},
  volume    = {85},
  number    = {3},
  pages     = {473--493},
  month     = may,
  doi       = {10.1111/insr.12217},
  publisher = {Wiley},
}

@Book{Ben08a,
  Title                    = {Wireless {P}ositioning {T}echnologies and {A}pplications},
  Author                   = {Alan Bensky},
  Publisher                = {Artech House},
  Year                     = {2008},

  File                     = {:Bensky - 2008 - Wireless Positioning Technologies and Applications.pdf:PDF},
  ISBN                     = {978-1-59693-130-5}
}

@Article{BenLuThoGarSch11a,
  author    = {Linus Bengtsson and Xin Lu and Anna Thorson and Richard Garfield and Johan von Schreeb},
  title     = {Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti},
  journal   = {{PLoS} Medicine},
  year      = {2011},
  volume    = {8},
  number    = {8},
  pages     = {e1001083},
  month     = aug,
  doi       = {10.1371/journal.pmed.1001083},
  editor    = {Peter W. Gething},
  file      = {:BenLuThoGarSch11a - Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data_ a Post Earthquake Geospatial Study in Haiti.pdf:PDF},
  publisher = {Public Library of Science ({PLoS})},
}

@InProceedings{BenGarKes05a,
  Title                    = {Secure Multi-Party Computation with Security Modules},
  Author                   = {Zinaida Benenson and Felix C. G{\"{a}}rtner and Dogan Kesdogan},
  Booktitle                = {Sicherheit 2005},
  Year                     = {2005},

  Address                  = {Regensburg, Germany},
  Editor                   = {Hannes Federrath},
  Organization             = {Gesellschaft f \"{u}r Informatik (GI)},
  Pages                    = {41--52},
  Series                   = {Lecture Notes in Informatics},
  Volume                   = {62},

  Abstract                 = {We consider the problem of secure multi-party computation (SMC) in a new
model where individual processes contain a tamper-proof security module. Security
modules can be trusted by other processes and can establish secure channels between
each other. However, their availability is restricted by their host, i.e., a corrupted party
can stop the computation of its own security module as well as drop any message sent
by or to its security module. In this model we show that SMC is solvable if and only
if a majority of processes is correct. We prove this by relating SMC to the problem of
Uniform Interactive Consistency among security modules (a variant of the Byzantine
Generals Problem from the area of fault-tolerance). The obtained solutions to SMC
for the first time allow to compute any function securely with a complexity which is
polynomial only in the number of processes (i.e., the complexity does not depend on
the function which is computed). We conclude that adding secure hardware does not
improve the resilience of SMC but can effectively improve the efficiency.},
  File                     = {:BenGarKes05a - Zinaida Benenson and Felix C. G{__{a}}rtner and Dogan Kesdogan.pdf:PDF}
}

@Article{BelKerChaBel16a,
  author    = {Aissam Belghiat and Elhillali Kerkouche and Allaoua Chaoui and Mokhtar Beldjehem},
  title     = {Mobile Agent-Based Software Systems Modeling Approaches: A Comparative Study},
  journal   = {Journal of Computing and Information Technology},
  year      = {2016},
  volume    = {24},
  number    = {2},
  pages     = {149--163},
  month     = jun,
  abstract  = {Mobile agent-based applications are special type of
software systems which take the advantages of mobile
agents in order to provide a new beneficial paradigm
to solve multiple complex problems in several fields
and areas such as network management, e-commerce,
e-learning, etc. Likewise, we notice lack of real applications
based on this paradigm and lack of serious
evaluations of their modeling approaches. Hence, this
paper provides a comparative study of modeling approaches
of mobile agent-based software systems. The
objective is to give the reader an overview and a thorough
understanding of the work that has been done
and where the gaps in the research are.},
  doi       = {10.20532/cit.2016.1002695},
  publisher = {Faculty of Electrical Engineering and Computing, Univ. of Zagreb},
}

@Article{BecVolCacHanIsaLohMarRowUrbVar13a,
  author    = {Richard Becker and Chris Volinsky and Ram{\'{o}}n C{\'{a}}ceres and Karrie Hanson and Sibren Isaacman and Ji Meng Loh and Margaret Martonosi and James Rowland and Simon Urbanek and Alexander Varshavsky},
  title     = {Human mobility characterization from cellular network data},
  journal   = {Communications of the {ACM}},
  year      = {2013},
  volume    = {56},
  number    = {1},
  pages     = {74},
  month     = jan,
  doi       = {10.1145/2398356.2398375},
  publisher = {Association for Computing Machinery ({ACM})},
}

@Article{BecCacHanLohUrbVarVol11a,
  author    = {R.A. Becker and R. C\'{a}ceres and K. Hanson and J.M. Loh and S. Urbanek and A. Varshavsky and C. Volinsky},
  title     = {A {T}ale of {O}ne {C}ity: {U}sing {C}ellular {N}etwork {D}ata for {U}rban {P}lanning},
  journal   = {{IEEE} Pervasive Computing},
  year      = {2011},
  volume    = {10},
  number    = {4},
  pages     = {18--26},
  month     = apr,
  booktitle = {18 PERVASIVE computing Published by the IEEE CS n},
  doi       = {10.1109/MPRV.2011.44},
  file      = {:BecCacHanLohUrbVarVol11a - A Tale of One City Using Cellular Network Data for Urban Planning.pdf:PDF},
  publisher = {IEEE},
}

@Misc{BecCacHanLohUrbVarVol11b,
  Title                    = {Route {C}lassification {U}sing {C}ellular {H}andoff {P}atterns},

  Author                   = {Richard A. Becker and Ram\'{o}n C\'{a}ceres and Karrie Hanson and Ji-Meng Loh and Simon Urbanek and Alexander Varshavsky and Chris Volinsky},
  HowPublished             = {Paper Session: On the Move. UbiComp'11 / Beijing, China},
  Year                     = {2011},

  Abstract                 = {Understanding utilization of city roads is important for urban planners. In this paper, we show how to use hand},
  Booktitle                = {Proceedings of the 13\textsuperscript{th} international conference on Ubiquitous computing - {UbiComp} {\textquotesingle}11},
  Doi                      = {10.1145/2030112.2030130},
  File                     = {:BecCacHanLohUrbVarVol11b - Richard A. Becker and Ram_'{o}n C_'{a}ceres and Karrie Hanson and Ji-Meng Loh and Simon Urbanek and Alexander Varshavsky and Chris Volinsky.pdf:PDF},
  Publisher                = {{ACM} Press}
}

@Misc{BawCavi11a,
  Title                    = {Sensing the urban: using location-based social network data in urban analysis},

  Author                   = {Anil Bawa-Cavia},
  Year                     = {2011},

  Abstract                 = {Location-based services (LBS) are generating vast bodies of data relating to the whereabouts of their users.
This is due to the ease with which modern mobile phones can communicate their precise location via the global posi-
tioning system (GPS). Online social networks have begun using LBS to aid social encounter and place discovery in cities.
A spatial analysis of the aggregate activity generated by such networks can show us how social activity in a city is dis-
tributed, revealing fine-grained spatial patterns evident in the social life of cities. The nature of this new data is discussed
in relation to existing urban data sets. Large-scale data from one such network is analysed across three cities in order
to produce an inter-urban analysis. Comparative measures of polycentricity and fragmentation are used to discuss the
spatial structure of the three cities in question. Finally, the impact of LBS technologies are discussed in the context of
urban analysis.},
  File                     = {:BawCavi11a - Anil Bawa-Cavia.pdf:PDF},
  Keywords                 = {Pervasive, computing, spatial analysis, social network, location-based service, urbanism, sensing}
}

@Article{BauKoeDeySan18a,
  author    = {Paul Baumann and Christian Koehler and Anind K. Dey and Silvia Santini},
  title     = {Selecting Individual and Population Models for Predicting Human Mobility},
  journal   = {{IEEE} Transactions on Mobile Computing},
  year      = {2018},
  volume    = {17},
  number    = {10},
  pages     = {2408--2422},
  month     = oct,
  doi       = {10.1109/tmc.2018.2797937},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{BarZheGezVee08a,
  author    = {Richard J Barton and Rong Zheng and Sinan Gezici and Venugopal V Veeravalli},
  title     = {Signal Processing for Location Estimation and Tracking in Wireless Environments},
  journal   = {{EURASIP} Journal on Advances in Signal Processing},
  year      = {2008},
  volume    = {2008},
  number    = {1},
  pages     = {356546},
  doi       = {10.1155/2008/356546},
  publisher = {Springer Nature},
}

@PhdThesis{Ban18a,
  Title                    = {Complex Human and Routine Behaviors Computational Method for Understanding},
  Author                   = {N. Banovic},
  School                   = {School of Computer Science. Carnegie Mellon University},
  Year                     = {2018},
  Month                    = jun,
  Type                     = {PhD Thesis},

  File                     = {:Ban18a - N. Banovic.pdf:PDF},
  Url                      = {https://figshare.com/articles/Computational_Method_for_Understanding_Complex_Human_Routine_Behaviors/7188812}
}

@Article{BanManViz09a,
  author    = {Bandini, Stefania and Manzoni, Sara and Vizzari, Giuseppe},
  title     = {Agent Based Modeling and Simulation: An Informatics Perspective},
  journal   = {Journal of Artificial Societies and Social Simulation},
  year      = {2009},
  volume    = {12},
  number    = {4},
  pages     = {4},
  issn      = {1460-7425},
  abstract  = {The term computer simulation is related to the usage of a computational model in order to improve the understanding of a system's behavior and/or to evaluate strategies for its operation, in explanatory or predictive schemes. There are cases in which practical or ethical reasons make it impossible to realize direct observations: in these cases, the possibility of realizing 'in-machina' experiments may represent the only way to study, analyze and evaluate models of those realities. Different situations and systems are characterized by the presence of autonomous entities whose local behaviors (actions and interactions) determine the evolution of the overall system; agent-based models are particularly suited to support the definition of models of such systems, but also to support the design and implementation of simulators. Agent-Based models and Multi-Agent Systems (MAS) have been adopted to simulate very different kinds of complex systems, from the simulation of socio-economic systems to the elaboration of scenarios for logistics optimization, from biological systems to urban planning. This paper discusses the specific aspects of this approach to modeling and simulation from the perspective of Informatics, describing the typical elements of an agent-based simulation model and the relevant research.},
  keywords  = {Multi-Agent Systems, Agent-Based Modeling and Simulation},
  publisher = {{\copyright}Copyright JASSS},
  url       = {http://jasss.soc.surrey.ac.uk/12/4/4.html},
}

@Article{BalBraBriCri18a,
  author    = {Caterina Balzotti and Andrea Bragagnini and Maya Briani and Emiliano Cristiani},
  title     = {Understanding Human Mobility Flows from Aggregated Mobile Phone Data {\^{a}}�{{\v{Z}}} {\^{a}}�{{\v{Z}}}This work was supported by funding from project {MIE} - Mobilit{\`{a}} Intelligente Ecosostenibile ({CTN}01{\_}00034{\_}594122), Cluster {\textquotedblleft}Tec-nologie per le Smart Communities{\textquotedblright}.},
  journal   = {{IFAC}-{PapersOnLine}},
  year      = {2018},
  volume    = {51},
  number    = {9},
  pages     = {25--30},
  doi       = {10.1016/j.ifacol.2018.07.005},
  file      = {:BalBraBriCri18a - Caterina Balzotti and Andrea Bragagnini and Maya Briani and Emiliano Cristiani.pdf:PDF;:BalBraBriCri18a (2).pdf:PDF},
  publisher = {Elsevier {BV}},
}

@Article{BakDaa11a,
  author    = {Bart F. M. Bakker and Piet J. H. Daas},
  title     = {Methodological challenges of register-based research},
  journal   = {Statistica Neerlandica},
  year      = {2011},
  volume    = {66},
  number    = {1},
  pages     = {2--7},
  month     = nov,
  doi       = {10.1111/j.1467-9574.2011.00505.x},
  publisher = {Wiley},
}

@Article{BajDelPanPetTiz15a,
  author    = {Paolo Bajardi and Matteo Delfino and Andr{\'{e}} Panisson and Giovanni Petri and Michele Tizzoni},
  title     = {Unveiling patterns of international communities in a global city using mobile phone data},
  journal   = {{EPJ} Data Science},
  year      = {2015},
  volume    = {4},
  number    = {1},
  month     = apr,
  doi       = {10.1140/epjds/s13688-015-0041-5},
  file      = {:BajDelPanPetTiz15a - Unveiling Patterns of International Communities in a Global City Using Mobile Phone Data.pdf:PDF},
  publisher = {Springer Nature},
}

@InProceedings{BahOltRai17a,
  author    = {Fran{\c{c}}oise Bahoken and Ana-Maria Olteanu-Raimond},
  title     = {Designing Origin-Destination Flow Matrices from Individual Mobile Phone Paths: The effect of spatiotemporal filtering on flow measurement},
  booktitle = {{ICC'13 - 26\textsuperscript{th} International Cartographic Conference}},
  year      = {2017},
  note      = {ICC'13 - 26\textsuperscript{th} International Cartographic Conference, DRESDEN, ALLEMAGNE, 25-/08/2013 - 30/08/2013},
  file      = {:BahOltRai17a - Designing Origin Destination Flow Matrices from Individual Mobile Phone Paths_ the Effect of Spatiotemporal Filtering on Flow Measurement.pdf:PDF},
  url       = {https://hal.archives-ouvertes.fr/hal-01011987},
}

@Article{AzaDonBenRocMas08a,
  author    = {R. Azaro and M. Donelli and M. Benedetti and P. Rocca and A. Massa},
  title     = {A {GSM} signals-based positioning technique for mobile applications},
  journal   = {Microwave and Optical Technology Letters},
  year      = {2008},
  volume    = {50},
  number    = {8},
  pages     = {2128--2130},
  doi       = {10.1002/mop.23568},
  publisher = {Wiley},
}

@Article{AraFanMatShi16a,
  author    = {Ayumi Arai and Zipei Fan and Dunstan Matekenya and Ryosuke Shibasaki},
  title     = {Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users},
  journal   = {{ISPRS} International Journal of Geo-Information},
  year      = {2016},
  volume    = {5},
  number    = {6},
  pages     = {85},
  month     = jun,
  doi       = {10.3390/ijgi5060085},
  file      = {:AraFanMatShi16a - Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users.pdf:PDF},
  publisher = {{MDPI} {AG}},
}

@Article{AniArdBelDamRea11a,
  author    = {Marco Anisetti and Claudio A. Ardagna and Valerio Bellandi and Ernesto Damiani and Salvatore Reale},
  title     = {Map-{B}ased {L}ocation and {T}racking in {M}ultipath {O}utdoor {M}obile {N}etworks},
  journal   = {{IEEE} Transactions on Wireless Communications},
  year      = {2011},
  volume    = {10},
  number    = {3},
  pages     = {814--824},
  month     = mar,
  doi       = {10.1109/twc.2011.011811.100025},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Article{AndOrdMedFou18a,
  author    = {Cuauhtemoc Anda and Sergio A. Ordo\~{n}ez Medina and Pieter Fourie},
  title     = {Multi-agent urban transport simulations using {OD} matrices from mobile phone data},
  journal   = {Procedia Computer Science},
  year      = {2018},
  volume    = {130},
  pages     = {803--809},
  doi       = {10.1016/j.procs.2018.04.139},
  publisher = {Elsevier {BV}},
}

@Article{AltShmZysLedOliPen14a,
  author    = {Y. Altshuler and E. Shmueli and G. Zyskind and O. Lederman and N. Oliver and A. Pentland},
  title     = {Campaign optimization through behavioral modeling and mobile network analysis},
  journal   = {{IEEE} Transactions on Computational Social Systems},
  year      = {2014},
  volume    = {1},
  number    = {2},
  pages     = {121--134},
  month     = jun,
  abstract  = {Optimizing the use of available resources is one of the key different populations located in different environments would
challenges in activities that consist of interactions with a large number of be tailored with different campaign strategies, the optimality
{\textquotedblleft}target individuals{\textquotedblright}, with the ultimate goal of {\textquotedblleft}winning{\textquotedblright} as many of them of each strategy would be maintained.
as possible, such as in marketing, service provision, political campaigns, A major contribution in our optimization model is the use
or homeland security. Typically, the cost of interactions is monotonically of network analysis methods to approximate the reach of a
increasing such that a method for maximizing the performance of these campaign. More specifically, given the network of mobility
campaigns is required. In this paper we propose a mathematical model between the different geographic locations, and a subset of
to compute an optimized campaign by automatically determining the locations, we use the Group Betweenness Centrality (GBC)
number of interacting units and their type, and how they should be [54] -- a network measure that calculates the percentage of
allocated to different geographical regions in order to maximize the
campaign{\textquoteright}s performance. We validate our proposed model using real shortest paths among all pairs of network nodes that pass
world mobility data. through a pre-defined sub-set of the network{\textquoteright}s nodes -- to},
  doi       = {10.1109/TCSS.2014.2377831},
  keywords  = {Mobile Networks, Network Optimization, Marketing, Behav- demonstrate that this function can be approximated using a ior Modeling smooth and easily analyzed Gompertz function. This tackles},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@TechReport{All10a,
  author      = {R.J. Allan},
  title       = {Survey of Agent and Based Modelling and Simulation Tools. Technical Report DL-TR},
  institution = {Science \& Technology. Facilities Council},
  year        = {2010},
  month       = oct,
}

@Misc{AliLoyColLepSaiSir08a,
  author = {S. Ali-L\"{o}ytty and J. Collin and H. Lepp\"{a}koski and H. Sairo and N. Sirola},
  title  = {MAT45806 Mathematics for Positioning and TKT-2546 Methods for Positioning},
  year   = {2421},
}

@Article{Algizawy2017,
  author    = {Essam Algizawy and Tetsuji Ogawa and Ahmed El-Mahdy},
  title     = {Real-Time Large-Scale Map Matching Using Mobile Phone Data},
  journal   = {{ACM} Transactions on Knowledge Discovery from Data},
  year      = {2017},
  volume    = {11},
  number    = {4},
  pages     = {1--38},
  month     = jul,
  doi       = {10.1145/3046945},
  publisher = {Association for Computing Machinery ({ACM})},
}

@Article{AleJiaMurGon15a,
  author    = {Lauren Alexander and Shan Jiang and Mikel Murga and Marta C. Gonz{\'{a}}lez},
  title     = {Origin{\textendash}destination trips by purpose and time of day inferred from mobile phone data},
  journal   = {Transportation Research Part C: Emerging Technologies},
  year      = {2015},
  volume    = {58},
  pages     = {240--250},
  month     = sep,
  doi       = {10.1016/j.trc.2015.02.018},
  file      = {:AleJiaMurGon15a - Origin-destination Trips by Purpose and Time of Day Inferred from Mobile Phone Data.pdf:PDF},
  publisher = {Elsevier {BV}},
}

@Misc{AlaAlkAlsAlfAlaRag15a,
  author       = {Z. Alawwad and W. Alkowaileet and S. Alsubaiee and A. Alfaris and M.M. Alansari and A.M. Ragab},
  title        = {Analyzing Call Detail Records to Support Tourism Statistics in {S}audi {A}rabia: An Exploratory Study},
  howpublished = {14\textsuperscript{th} Global Forum on Tourism Statistics},
  year         = {2015},
  abstract     = {Following the dramatic rise in data collection in recent years, considerable attention has been directed towards adopting innovative methods to compile tourism statistics from nontraditional sources. Many initiatives have emerged globally that adopt big data sources for tourism statistics (e.g. mobile positioning data, booking and ticketing data, web searches, social media, etc). The purpose of this paper is to explore the potential use of call detail records (CDRs) as auxiliary sources for reinforcing and improving the quality of tourism statistics in Saudi Arabia. Using CDR data, the Center for Complex Engineering Systems at KACST and MIT has identified the home locations of anonymous users and analyzed their movement patterns to analyze the destinations of domestic tourists from various cities throughout the country. We use this to determine the flow of tourists between administrative regions and compare the results to statistics collected from traditional facetoface surveys. Additionally, we explore popular destinations for domestic tourists and demonstrate how the sources of tourists can be used to study attractions that are commonly visited by people who live farther away and compare them to destinations that typically receive visitors from nearby cities. Finally, the positions of tourists can be examined in detail to reveal the precise locations of tourist attractions. The possibility of using these passive mobile positioning data for supporting traditional domestic tourism surveys is discussed with the intention of serving the Tourism Statistics System (STS) in Saudi Arabia.
{~}{~}},
  file         = {:AlaAlkAlsAlfAlaRag15a - Analyzing Call Detail Records to Support Tourism Statistics in Saudi Arabia_ an Exploratory Study.pdf:PDF},
  url          = {http://tsf2016venice.enit.it/images/articles/Papers_Forum/1.3_Analyzing%20Call%20Detail%20Records%20to%20Support%20Tourism%20Statistics%20in%20Saudi%20Arabia%20-%20An%20Exploratory%20Study.pdf},
}

@Article{AlaBenTogSoh17a,
  author    = {Mohammad Rafiqul Alam and Mohammed Bennamoun and Roberto Togneri and Ferdous Sohel},
  title     = {A Joint Deep Boltzmann Machine ({jDBM}) Model for Person Identification Using Mobile Phone Data},
  journal   = {{IEEE} Transactions on Multimedia},
  year      = {2017},
  volume    = {19},
  number    = {2},
  pages     = {317--326},
  month     = feb,
  doi       = {10.1109/tmm.2016.2615524},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@InProceedings{Aki13a,
  author    = {Y. Akiyama},
  title     = {Evaluation analysis of estimation of population distribution by DMSP/OLS satellite images using GPS log data of mobile phones},
  booktitle = {34\textsuperscript{th} Asian Conference on Remote Sensing 2013, ACRS 2013},
  year      = {2013},
  volume    = {5},
  pages     = {4042--4049},
  address   = {Bali, Indonesia},
  month     = oct,
}

@Article{AhmYaqHasShuImrGuiBak18a,
  author    = {Ejaz Ahmed and Ibrar Yaqoob and Ibrahim Abaker Targio Hashem and Junaid Shuja and Muhammad Imran and Nadra Guizani and Sheikh Tahir Bakhsh},
  title     = {Recent Advances and Challenges in Mobile Big Data},
  journal   = {{IEEE} Communications Magazine},
  year      = {2018},
  volume    = {56},
  number    = {2},
  pages     = {102--108},
  month     = feb,
  doi       = {10.1109/mcom.2018.1700294},
  publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
}

@Misc{AhaTirSalDeM14a,
  author = {Rein Ahas and Margus Tiru and Erki Saluveer and Christophe Demunter},
  title  = {Mobile telephones and mobile positioning data as source for statistics: Estonian experiences},
  year   = {2014},
  file   = {:AhaTirSalDeM14a - Mobile Telephones and Mobile Positioning Data As Source for Statistics_ Estonian Experiences.pdf:PDF},
}

@Article{AhaSilJarSalTir10c,
  author    = {Rein Ahas and Siiri Silm and Olle J{\"{a}}rv and Erki Saluveer and Margus Tiru},
  title     = {Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones},
  journal   = {Journal of Urban Technology},
  year      = {2010},
  volume    = {17},
  number    = {1},
  pages     = {3--27},
  month     = apr,
  doi       = {10.1080/10630731003597306},
  publisher = {Informa {UK} Limited},
}

@Article{AhaAasYuaRauSmoLiuZieTirZoo15a,
  author    = {R. Ahas and A. Aasa and Y. Yuan and M. Raubal and Z. Smoreda and Y. Liu and C. Ziemlicki and M. Tiru and M. Zook},
  title     = {Everyday space{\textendash}time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn},
  journal   = {International Journal of Geographical Information Science},
  year      = {2015},
  volume    = {29},
  number    = {11},
  pages     = {2017--2039},
  month     = jul,
  doi       = {10.1080/13658816.2015.1063151},
  publisher = {Informa {UK} Limited},
}

@Article{AhaAasSilTir10a,
  author    = {Rein Ahas and Anto Aasa and Siiri Silm and Margus Tiru},
  title     = {Daily rhythms of suburban commuters' movements in the Tallinn metropolitan area: Case study with mobile positioning data},
  journal   = {Transportation Research Part C: Emerging Technologies},
  year      = {2010},
  volume    = {18},
  number    = {1},
  pages     = {45--54},
  month     = feb,
  doi       = {10.1016/j.trc.2009.04.011},
  publisher = {Elsevier {BV}},
}

@InProceedings{AhaAasSilTir07a,
  author    = {Rein Ahas and Anto Aasa and Siiri Silm and Margus Tiru},
  title     = {Mobile Positioning Data in Tourism Studies and Monitoring: Case Study in Tartu, Estonia},
  booktitle = {Proceedings of the International Conference Information and Communication Technologies in Tourism, ENTER 2007},
  year      = {2007},
  address   = {Ljubljana, Slovenia},
  file      = {:Ahasetal_2007_MobilePositioningDatainTourismStudiesandMonitoringCaseStudyinTartuEstonia.pdf:PDF},
}

@Article{AhaAasSilAunKalMar07a,
  author    = {R. Ahas and A. Aasa and S. Silm and R. Aunap and H. Kalle and \"{U}. Mark},
  title     = {Mobile Positioning in Space-Time Behaviour Studies: Social Positioning Method Experiments in Estonia},
  journal   = {Cartography and Geographic Information Science},
  year      = {2007},
  volume    = {34},
  number    = {4},
  pages     = {259--273},
  month     = jan,
  doi       = {10.1559/152304007782382918},
  file      = {:AhaAasSilAunKalMar07a - Mobile Positioning in Space Time Behaviour Studies_ Social Positioning Method Experiments in Estonia.pdf:PDF},
  publisher = {Informa {UK} Limited},
}

@Article{AhaAasRooMarSil08a,
  author    = {R. Ahas and A. Aasa and A. Roose and \"{U}. Mark and S. Silm},
  title     = {Evaluating passive mobile positioning data for tourism surveys: {A}n {E}stonian case study},
  journal   = {Tourism Management},
  year      = {2008},
  volume    = {29},
  number    = {3},
  pages     = {469--486},
  month     = jun,
  doi       = {10.1016/j.tourman.2007.05.014},
  publisher = {Elsevier {BV}},
}

@Article{AhaAasMarPaeKul07a,
  author    = {Rein Ahas and Anto Aasa and {{\"{U}}}lar Mark and Taavi Pae and Ain Kull},
  title     = {Seasonal tourism spaces in {E}stonia: {C}ase study with mobile positioning data},
  journal   = {Tourism Management},
  year      = {2007},
  volume    = {28},
  number    = {3},
  pages     = {898--910},
  month     = jun,
  abstract  = {The study analysed the seasonality of foreign tourists{\textquoteright} space consumption in Estonia using mobile positioning dataset with anonymous
roaming data. The method which uses mobile phone positioning coordinates in space--time movement studies in Estonia is called the social
positioning method. The dataset allowed analysis of the distribution of foreigners{\textquoteright} country of origin in Estonia with the precision of
network cells of mobile operators. Privacy of mobile phone holders was guaranteed according to EU regulation. It was concluded that
seasonality produces very different and sometimes even opposite tourists{\textquoteright} space consumption patterns in Estonia. Coastal areas are popular
for summer tourism and not so popular in winter; continental inland areas were used more for winter tourism. The popular summer tourism
areas along the Baltic Sea beaches are dominated by one nationality: the Finnish in western Estonia, and the Russians in eastern Estonia.
Latvians made up a higher percentage in Saaremaa and P\"{a}rnu during summer and in Otep\"{a}\"{a} and Lake Peipsi in winter. The mobile
positioning data have great potential for tourism studies and monitoring, but is a sensitive issue due to the fear of surveillance.},
  doi       = {10.1016/j.tourman.2006.05.010},
  publisher = {Elsevier {BV}},
}

@Article{Aha10a,
  author    = {Rein Ahas},
  title     = {From the Guest Editor: Mobile Positioning and Tracking in Geography and Planning},
  journal   = {Journal of Urban Technology},
  year      = {2010},
  volume    = {17},
  number    = {1},
  pages     = {1--2},
  month     = apr,
  doi       = {10.1080/10630731003597298},
  publisher = {Informa {UK} Limited},
}

@Article{vAcNeu15a,
  author   = {Veronique van Acker and Tijs Neutens},
  title    = {Editorial: Moving and forward with mobile positioning data in academic research},
  journal  = {European Journal of Transport and Infrastructure Research, [S.l.]},
  year     = {2015},
  volume   = {15},
  number   = {4},
  month    = sep,
  doi      = {10.18757/ejtir.2015.15.4.3101},
  keywords = {mobile positioning, location-based services, GPS, smartphone, travel behaviour},
}

@Proceedings{D4D14a,
  Title                    = {Data for Development Challenge Senegal},
  Year                     = {2014},
  Editor                   = {Orange},

  Author                   = {{Book of Abstracts and Posters}},
  File                     = {:D4D14a - {Book of Abstracts and Posters}.pdf:PDF}
}

@Article{AbaTheLemOHa17a,
  author    = {Sameera Abar and Georgios K. Theodoropoulos and Pierre Lemarinier and Gregory M.P. O'Hare},
  title     = {Agent Based Modelling and Simulation tools: A review of the state-of-art software},
  journal   = {Computer Science Review},
  year      = {2017},
  volume    = {24},
  pages     = {13--33},
  month     = may,
  doi       = {10.1016/j.cosrev.2017.03.001},
  publisher = {Elsevier {BV}},
}

@Comment{jabref-meta: databaseType:bibtex;}

@Comment{jabref-meta: saveActions:enabled;
date[normalize_date]
pages[normalize_page_numbers]
month[normalize_month]
all-text-fields[identity,html_to_latex,unicode_to_latex,ordinals_to_superscript]
;}

@Comment{jabref-meta: saveOrderConfig:specified;author;true;year;true;bibtexkey;true;}