[Forum SIS] UNIBO Statistics Seminars

[Silvia Cagnone]

We are glad to announce the following Statistics Seminar:


Thursday, April 6th, 2017

Room II, 2:30 p.m.
Department of Statistical Sciences
via delle Belle Arti 41, Bologna

Laura M. Sangalli (Politecnico di Milano)


Functional Data Analysis, Spatial Data Analysis and Partial Differential Equations: a fruitful union

Abstract: I will present a novel class of models for the analysis of spatially (or space-time) distributed data, based on the idea of regression with differential regularizations. The models merge statistical methodology and advanced numerical analysis techniques. Thanks to the combination of potentialities from these different scientific areas, the proposed method has important advantages with respect to classical spatial data analysis techniques. Spatial Regression with differential regularizations is able to efficiently deal with data distributed over complex planar domains as well as over manifold domains. Moreover, it can comply with specific conditions at the boundaries of the problem domain, which is fundamental in many applications to obtain meaningful estimates. The proposed models can also incorporate problem-specific priori information about the spatial (or space-time) structure of the phenomenon under study,  naturally accounting for anisotropy and non-stationarity. The use of advanced numerical analysis techniques, and in particular of the finite element method or of isogeometric analysis, makes the models computationally very efficient.

Based on joint work with John Aston, Laura Azzimonti, Mara Bernardi, Bree Ettinger, Michelle Carey, Eardi Lila, Fabio Nobile, Simona Perotto, Jim Ramsay, Piercesare Secchi.


Contact person: Alessandra Luati


The schedule of the statistics seminars are available at http://www.stat.unibo.it/it/dipartimento/seminari-di-statistica-2017


Silvia Cagnone
Department of Statistical Sciences "Paolo Fortunati"
University of Bologna
Via delle Belle Arti 41 - 40126  Bologna,  ITALY
Tel: +39 051 2098213  Fax: +39 051 232153
http://www2.stat.unibo.it/cagnone/

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