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Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization

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Functional and High-Dimensional Statistics and Related Fields (IWFOS 2020)

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

We apply spatio-temporal regression with partial differential equation regularization to the Telecom Italia mobile phone data. The technique proposed allows to include specific information on the phenomenon under study through a definition of the non-stationary anisotropy characterizing the spatial regularization based on the texture of the domain on which the data are observed.

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Author information

Authors and Affiliations

  1. MOX - Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy

    Eleonor Arnone, Mara S. Bernardi, Laura M. Sangalli & Piercesare Secchi

Authors
  1. Eleonor Arnone
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  2. Mara S. Bernardi
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  3. Laura M. Sangalli
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  4. Piercesare Secchi
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Corresponding author

Correspondence to Mara S. Bernardi .

Editor information

Editors and Affiliations

  1. Department of Mathematics, University of A Coruña, A Coruña, Spain

    Germán Aneiros

  2. Department of Mathematics and Statistics, Masaryk University, Brno, Czech Republic

    Ivana Horová

  3. Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic

    Marie Hušková

  4. Toulouse Mathematics Institute, Paul Sabatier University - Toulouse III, Toulouse, France

    Philippe Vieu

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Arnone, E., Bernardi, M.S., Sangalli, L.M., Secchi, P. (2020). Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization. In: Aneiros, G., Horová, I., Hušková, M., Vieu, P. (eds) Functional and High-Dimensional Statistics and Related Fields. IWFOS 2020. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-47756-1_2

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