Jueves, 29 de Octubre de 2015
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16:05-16:55 Nan-Jun Hsu
(40 min + 10 min) Semiparametric estimation and selection for nonstationary spatial-temporal covariance functions
Abstract

We propose a new method for estimating nonstationary spatial-temporal covariance functions by representing a spatial-temporal process as a linear combination of a stationary spatialtemporal process and some local basis functions in space with temporal-dependent coefficients. By incorporating a large number of local basis functions with various scales at various locations, the resulting model is flexible to represent a wide variety of nonstationary spatial-temporal features. We consider the sample covariances as the response and formulate the covariance function estimation as a constrained least squares problem. This allows us to select appropriate basis functions and estimate the parameters simultaneously. Some numerical examples are given to show the effectiveness of the proposed method.

16:55-17:30 Nicolis, O., Mateu, J. and D'Ercole, R.
(25 min + 10 min) Testing for anisotropy in spatial point processes
 
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