[Forum SIS] Avviso di seminario :: Sangalli a DSS (Scienze Statistiche, Sapienza)

[Pierpaolo Brutti]

*Sapienza Università di Roma*
Dipartimento di Scienze Statistiche

*Dottorato di Ricerca in Scienze Statistiche*
(curric: Statistica Metodologica)


 *Laura Sangalli*
MOX, Dipartimento di Matematica
Politecnico di Milano

*Statistical and Numerical techniques for Spatial Functional Data Analysis*
Venerdì 22 Novembre 2013, ore 11
Sala 34, Dipartimento di Scienze Statistiche, Sapienza
(Piazzale A. Moro, 5 - Roma)

Cordiali saluti,
Pierpaolo Brutti - Fulvio De Santis

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*Summary*
I will present a novel class of models for the accurate estimation of
surfaces and spatial fields, that merges advanced statistical methodology
with numerical analysis techniques.
Thanks to the combination of potentialities from these two scientific
areas, the proposed class of models has important advantages with respect
to classical techniques used in spatial data analysis.

The models are able to efficiently deal with data distributed over
irregularly shaped domains, including Riemannian manifold domains, only few
methods existing in literature for this type of data structures. Moreover,
they can incorporate problem-specific priori information about the spatial
structure of the phenomenon under study, with a very flexible modeling of
space variation, allowing naturally for anisotropy and non-stationarity.
The models have a generalized additive framework with a regularizing term
involving a differential quantity of the surface of spatial field to be
estimated. The estimators have good inferential properties; moreover,
thanks to the use of numerical analysis techniques, they are
computationally highly efficient. The method is illustrated in various
applied contexts, including data coming from eco-dopplers,
three-dimensional angiographies and computational fluid dynamics
simulations.

The seminar is based on joint work with Laura Azzimonti, Bree Ettinger,
Fabio Nobile, Simona Perotto, Jim Ramsay, Piercesare Secchi.

This line of research is developed within the FIRB2008 Futuro in Ricerca
research project SNAPLE (http://mox.polimi.it/users/sangalli/firbSNAPLE.html
).
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