IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v24y2015i2p335-338.html
   My bibliography  Save this article

Rejoinder to the discussion of “Analysis of Spatio-Temporal Mobile Phone Data: a Case Study in the Metropolitan Area of Milan”

Author

Listed:
  • Piercesare Secchi
  • Simone Vantini
  • Valeria Vitelli

Abstract

The paper is the rejoinder to the discussion of “Analysis of Spatio-Temporal Mobile Phone Data: a Case Study in the Metropolitan Area of Milan”. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Piercesare Secchi & Simone Vantini & Valeria Vitelli, 2015. "Rejoinder to the discussion of “Analysis of Spatio-Temporal Mobile Phone Data: a Case Study in the Metropolitan Area of Milan”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 335-338, July.
    • Handle: RePEc:spr:stmapp:v:24:y:2015:i:2:p:335-338
    DOI: 10.1007/s10260-015-0325-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10260-015-0325-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10260-015-0325-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Orietta Nicolis & Jorge Mateu, 2015. "Discussion of the paper “analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 315-319, July.
    2. Piercesare Secchi & Simone Vantini & Valeria Vitelli, 2015. "Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 279-300, July.
    3. Aurea Grané & Rosario Romera, 2015. "Piercesare Secchi, Simone Vantini and Valeria Vitelli: Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 313-314, July.
    4. James Ramsay, 2015. "Discussion of Secchi, Vantini and Vitelli paper," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 301-304, July.
    5. Wenceslao González-Manteiga & Rosa Crujeiras, 2015. "Discussion on the paper “Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan” by P. Secchi, S. Vantini and V. Vitelli," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 325-327, July.
    6. Laura M. Sangalli & James O. Ramsay & Timothy O. Ramsay, 2013. "Spatial spline regression models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 681-703, September.
    7. Piotr Kokoszka, 2015. "P. Secchi, S. Vantini and V. Vitelli: Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 305-306, July.
    8. Anestis Antoniadis & Jean-Michel Poggi, 2015. "Discussion of “Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 307-312, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martha Bohorquez & Ramón Giraldo & Jorge Mateu, 2016. "Optimal sampling for spatial prediction of functional data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 39-54, March.
    2. Giraldo, Ramón & Dabo-Niang, Sophie & Martínez, Sergio, 2018. "Statistical modeling of spatial big data: An approach from a functional data analysis perspective," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 126-129.
    3. Alfredo Cartone & Domenica Panzera, 2021. "Deprivation at local level: Practical problems and policy implications for the province of Milan," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 43-61, February.
    4. Menafoglio, Alessandra & Secchi, Piercesare, 2017. "Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics," European Journal of Operational Research, Elsevier, vol. 258(2), pages 401-410.
    5. Orietta Nicolis & Jorge Mateu, 2015. "Discussion of the paper “analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 315-319, July.
    6. Rodolfo Metulini & Maurizio Carpita, 2021. "A Spatio-Temporal Indicator for City Users Based on Mobile Phone Signals and Administrative Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 761-781, August.
    7. Ding, Liang & Huang, Ziqian & Xiao, Chaowei, 2023. "Are human activities consistent with planning? A big data evaluation of master plan implementation in Changchun," Land Use Policy, Elsevier, vol. 126(C).
    8. Claudio Gariazzo & Armando Pelliccioni & Maria Paola Bogliolo, 2019. "Spatiotemporal Analysis of Urban Mobility Using Aggregate Mobile Phone Derived Presence and Demographic Data: A Case Study in the City of Rome, Italy," Data, MDPI, vol. 4(1), pages 1-25, January.
    9. Alessandro Fassò & Francesco Finazzi & Ferdinand Ndongo, 2016. "European Population Exposure to Airborne Pollutants Based on a Multivariate Spatio-Temporal Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 492-511, September.
    10. Xinxin Guo & Benyong Wei & Gaozhong Nie & Guiwu Su, 2022. "Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China," IJERPH, MDPI, vol. 19(17), pages 1-23, August.
    11. Pedro Delicado, 2015. "Discussion of “Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan” by Piercesare Secchi, Simone Vantini and Valeria Vitelli," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 329-333, July.
    12. Secchi, Piercesare, 2018. "On the role of statistics in the era of big data: A call for a debate," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 10-14.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Menafoglio, Alessandra & Secchi, Piercesare, 2017. "Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics," European Journal of Operational Research, Elsevier, vol. 258(2), pages 401-410.
    2. Giraldo, Ramón & Dabo-Niang, Sophie & Martínez, Sergio, 2018. "Statistical modeling of spatial big data: An approach from a functional data analysis perspective," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 126-129.
    3. Ferraccioli, Federico & Sangalli, Laura M. & Finos, Livio, 2022. "Some first inferential tools for spatial regression with differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    4. Claudio Gariazzo & Armando Pelliccioni & Maria Paola Bogliolo, 2019. "Spatiotemporal Analysis of Urban Mobility Using Aggregate Mobile Phone Derived Presence and Demographic Data: A Case Study in the City of Rome, Italy," Data, MDPI, vol. 4(1), pages 1-25, January.
    5. Alessandro Fassò & Francesco Finazzi & Ferdinand Ndongo, 2016. "European Population Exposure to Airborne Pollutants Based on a Multivariate Spatio-Temporal Model," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 492-511, September.
    6. Secchi, Piercesare, 2018. "On the role of statistics in the era of big data: A call for a debate," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 10-14.
    7. Aneiros, Germán & Cao, Ricardo & Fraiman, Ricardo & Genest, Christian & Vieu, Philippe, 2019. "Recent advances in functional data analysis and high-dimensional statistics," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 3-9.
    8. Christian Genest & Johanna G. Nešlehová, 2014. "A Conversation with James O. Ramsay," International Statistical Review, International Statistical Institute, vol. 82(2), pages 161-183, August.
    9. Arnone, Eleonora & Azzimonti, Laura & Nobile, Fabio & Sangalli, Laura M., 2019. "Modeling spatially dependent functional data via regression with differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 275-295.
    10. Rodolfo Metulini & Maurizio Carpita, 2021. "A Spatio-Temporal Indicator for City Users Based on Mobile Phone Signals and Administrative Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 761-781, August.
    11. Vieu, Philippe, 2018. "On dimension reduction models for functional data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 134-138.
    12. Nguyen, Hien D. & McLachlan, Geoffrey J., 2016. "Maximum likelihood estimation of triangular and polygonal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 23-36.
    13. Smirnova, Ekaterina & Khormali, Omid & Egan, Joel M., 2019. "Functional analysis of spatial aggregation regions of Jeffrey pine beetle-attack within the Lake Tahoe Basin," Statistics & Probability Letters, Elsevier, vol. 144(C), pages 57-62.
    14. Laura Azzimonti & Laura M. Sangalli & Piercesare Secchi & Maurizio Domanin & Fabio Nobile, 2015. "Blood Flow Velocity Field Estimation Via Spatial Regression With PDE Penalization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1057-1071, September.
    15. Martha Bohorquez & Ramón Giraldo & Jorge Mateu, 2016. "Optimal sampling for spatial prediction of functional data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 39-54, March.
    16. Dabo-Niang, S. & Guillas, S. & Ternynck, C., 2016. "Efficiency in multivariate functional nonparametric models with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 168-182.
    17. Alfredo Cartone & Domenica Panzera, 2021. "Deprivation at local level: Practical problems and policy implications for the province of Milan," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 43-61, February.
    18. Ding, Liang & Huang, Ziqian & Xiao, Chaowei, 2023. "Are human activities consistent with planning? A big data evaluation of master plan implementation in Changchun," Land Use Policy, Elsevier, vol. 126(C).
    19. Lee, Xing Ju & Hainy, Markus & McKeone, James P. & Drovandi, Christopher C. & Pettitt, Anthony N., 2018. "ABC model selection for spatial extremes models applied to South Australian maximum temperature data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 128-144.
    20. Bernardi, Mara S. & Carey, Michelle & Ramsay, James O. & Sangalli, Laura M., 2018. "Modeling spatial anisotropy via regression with partial differential regularization," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 15-30.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stmapp:v:24:y:2015:i:2:p:335-338. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.