Statistical Methods & Applications

, Volume 24, Issue 2, pp 325–327 | Cite as

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

  • Wenceslao González-Manteiga
  • Rosa M. CrujeirasEmail author


First of all, we would like to congratulate the authors for their interesting paper, a nice combination of methodological proposal and data analysis. This work is focused on geo-referenced high-dimensional data, with the purpose of identifying spatial and/or temporal patterns. After a first reading, one may think about possible applications of the proposed methodology in environmental sciences (e.g. pollutants concretation patterns), which certainly opens a fruitful application field. In this area, prediction surfaces can be produced by kriging methods adapted to functional data (see [1], for an application to temperature curves). Although prediction is usually the main goal, the identification of similar spatial and/or temporal patterns provides useful information for characterizing and understanding the behaviour of the (complex) underlying process, as it can be clearly seen in the example analyzed in this work.

We would like also to highlight the (purley nonparametric)...


Temporal Pattern Time Interaction Local Representative Aggregation Step Project Proposal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Caballero W, Giraldo R, Mateu J (2013) A universal kriging approach for spatial functional data. Stoch Env Res Risk Assess 27:1553–1563CrossRefGoogle Scholar
  2. 2.
    Breiman L (1996) Bagging predictors. Mach Learn 24:123–140MathSciNetzbMATHGoogle Scholar
  3. 3.
    Buhlmann P, Yu B (2002) Analyzing bagging. Ann Stat 30:927–961MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Wenceslao González-Manteiga
    • 1
  • Rosa M. Crujeiras
    • 1
    Email author
  1. 1.Department of Statistics and Operations ResearchUniversity of Santiago de CompostelaSantiago de CompostelaSpain

Personalised recommendations