Abstract
The authors are to be congratulated on a valuable and thought-provoking contribution on the analysis of geo-referenced high-dimensional data describing the use over time of the mobile-phone network in the urban area of Milan, Italy. This is a timely and world-wide problem that opens wide avenues for new methodological contributions. The authors develop a Bagging Voronoi Treelet Analysis which is a non-parametric method for the analysis of spatially dependent functional data. This approach integrates the treelet decomposition with a proper treatment of spatial dependence, obtained through a Bagging Voronoi strategy. In our discussion, we focus on the following points: (i) a mobre general form of the spatio-temporal model proposed in Secchi et al. (Stat Methods Appl, 2015), (ii) alternative methods to approach the smooth temporal functions, (iii) additional methods to reduce the problem of dimension for spatial dependence data, and (iv) comments on the pros and cons of the proposed pre-processing methodology.
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Acknowledgments
The present work has been partially supported by Fondecyt grant 1131147 from the Chilean government, and research funds of the University of Palermo with reference 2012-ATE-0332. Additionally, partial funding comes from grants P1-1B2012-52, and MTM2013-43917-P from Ministery of Economy and Competitivity.
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Nicolis, O., Mateu, J. Discussion of the paper “analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan”. Stat Methods Appl 24, 315–319 (2015). https://doi.org/10.1007/s10260-015-0311-1
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DOI: https://doi.org/10.1007/s10260-015-0311-1