[Forum SIS] DEC Seminar - September 25th

[Raffaella Piccarreta]

Dear all, 
we are glad to announce the following seminar 







DEC - Statistics Seminar 
Università Bocconi, 
Room 3-E4-SR03 
Via Rontgen 1 - 3rd floor 
Time: 12:30pm 
(The DEC seminar schedule is available at http://www.unibocconi.eu/statseminar ) 


Thursday, September 25th 



Elvira Romano 
(Seconda Università degli Studi di Napoli) 

Clustering functional data with spatial dependence 



Abstract 

This talk presents a clustering method for spatially correlated functional data [1], [2]. Its main feature is that it finds groups of functions homogeneous in terms of spatial functional variability. Moreover it detects a set of centers describing the spatial functional variability of each cluster. The method optimizes a best fit criterion between the partition of the curves and the representative element of the clusters, assumed to be a trace-variogram function for functional data. Performances of this method are compared and examined with a hierarchical method based on the same measure of spatial dependence. [3], [4]. In particular, the role of the spatial dependence computed by the trace-variogram function is analyzed. The main features of both procedures is shown through an intensive simulation study based on a variety of practical scenarios easily encountered in the analysis of spatial functional data. An application on real data is also presented. 

1. Romano, E., Balzanella, A., Verde, R. (2013). A regionalization method for spatial functional data based on variogram models: an application on environmental data. In Advances in Theoretical and Applied Statistics, (Eds.) Torelli, N., Pesarin, F., Bar-Hen, 
A. Springer. ISBN 978-3-642-35587-5. 
2. Romano, E., Balzanella, A., Verde, R. (2014). A clustering method for functional data with spatial dependence (submitted) 
3. ROMANO E, MATEU J, GIRALDO R (2011). Clustering spatially correlated functional data. In: (a cura di): Ferraty, Frédéric, Recent Advances in Functional Data Analysis and Related Topics Contributions to Statistics. BERLIN:Physica-Verlag. 
4. ROMANO E, MATEU J, GIRALDO R (2014). On the performance of two clustering methods for spatial functional data. (submitted) 
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Raffaella Piccarreta 
DEC - Department of Decision Sciences, 
Universita' L.Bocconi, via Guglielmo Röntgen 1 (3rd floor, room D1-09). 20136, Milano. 
email: piccarreta a unibocconi.it 
tel. +39-02-58365659 / fax +39-02-58365630 

Web page (ENGLISH VERSION): http://faculty.unibocconi.eu/raffaellapiccarreta/ 
(ITALIAN VERSION): http://faculty.unibocconi.it/raffaellapiccarreta/ 
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