A set of R packages to estimate population counts from mobile phone data

被引:0
|
作者
Oancea, Bogdan [1 ,2 ]
Salgado, David [3 ]
Sanguiao Sande, Luis [3 ]
Barragan, Sandra [3 ]
机构
[1] Natl Inst Stat, Bucharest, Romania
[2] Univ Bucharest, Bucharest, Romania
[3] Natl Inst Stat, Madrid, Spain
关键词
R; mobile phone data; population count; geolocation; deduplication; aggregation; inference;
D O I
暂无
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
In this paper, we describe the software implementation of the methodological framework designed to incorporate mobile phone data into the current production chain of official statistics during the ESSnet Big Data II project. We present an overview of the architecture of the software stack, its components, the interfaces between them, and show how they can be used. Our software implementation consists in four R packages: destim for estimation of the spatial distribution of the mobile devices, deduplication for classification of the devices as being in 1:1 or 2:1 correspondence with its owner, aggregation for estimation of the number of individuals detected by the network starting from the geolocation probabilities and the duplicity probabilities and inference which combines the number of individuals provided by the previous package with other information like the population counts from an official register and the mobile operator penetration rates to provide an estimation of the target population counts.
引用
收藏
页码:17 / 38
页数:22
相关论文
共 50 条
  • [21] From mobile phone data to the spatial structure of cities
    Thomas Louail
    Maxime Lenormand
    Oliva G. Cantu Ros
    Miguel Picornell
    Ricardo Herranz
    Enrique Frias-Martinez
    José J. Ramasco
    Marc Barthelemy
    Scientific Reports, 4
  • [22] RiSC: Quantifying change after natural disasters to estimate infrastructure damage with mobile phone data
    Andrade, Xavier
    Layedra, Fabricio
    Vaca, Carmen
    Cruz, Eduardo
    2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2018, : 3383 - 3391
  • [23] Phone Sharing and Cash Transfers in Togo: Quantitative Evidence from Mobile Phone Data
    Aiken, Emily L.
    Thakur, Viraj
    Blumenstock, Joshua E.
    PROCEEDINGS OF THE 4TH ACM SIGCAS/SIGCHI CONFERENCE ON COMPUTING AND SUSTAINABLE SOCIETIES, COMPASS'22, 2022, : 214 - 231
  • [24] Exploring methods for mapping seasonal population changes using mobile phone data
    Woods, D.
    Cunningham, A.
    Utazi, C. E.
    Bondarenko, M.
    Shengjie, L.
    Rogers, G. E.
    Koper, P.
    Ruktanonchai, C. W.
    Zu Erbach-Schoenberg, E.
    Tatem, A. J.
    Steele, J.
    Sorichetta, A.
    HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2022, 9 (01):
  • [25] Spatiotemporal Detection of Unusual Human Population Behavior Using Mobile Phone Data
    Dobra, Adrian
    Williams, Nathalie E.
    Eagle, Nathan
    PLOS ONE, 2015, 10 (03):
  • [26] Exploring methods for mapping seasonal population changes using mobile phone data
    D. Woods
    A. Cunningham
    C. E. Utazi
    M. Bondarenko
    L. Shengjie
    G. E. Rogers
    P. Koper
    C. W. Ruktanonchai
    E. zu Erbach-Schoenberg
    A. J. Tatem
    J. Steele
    A. Sorichetta
    Humanities and Social Sciences Communications, 9
  • [27] Urban Population Distribution Characteristics Analysis Method based on Mobile Phone Data
    Wu Dongdong
    Shi Ruixuan
    Wang Jiachuan
    Wu Shuqing
    PROCEEDINGS OF THE 2016 5TH INTERNATIONAL CONFERENCE ON ADVANCED MATERIALS AND COMPUTER SCIENCE, 2016, 80 : 57 - 64
  • [28] Data from mobile phone operators: A tool for smarter cities?
    Steenbruggen, John
    Tranos, Emmanouil
    Nijkamp, Peter
    TELECOMMUNICATIONS POLICY, 2015, 39 (3-4) : 335 - 346
  • [29] Complete trajectory reconstruction from sparse mobile phone data
    Guangshuo Chen
    Aline Carneiro Viana
    Marco Fiore
    Carlos Sarraute
    EPJ Data Science, 8
  • [30] Complete trajectory reconstruction from sparse mobile phone data
    Chen, Guangshuo
    Viana, Aline Carneiro
    Fiore, Marco
    Sarraute, Carlos
    EPJ DATA SCIENCE, 2019, 8 (01)