Abstract #300762

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JSM 2003 Abstract #300762
Activity Number: 158
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: ASA-SRCOS So. Regional Cmte on Stats Summer Research
Abstract - #300762
Title: Modeling and Testing for Lack of Separability of Spatial-Temporal Processes
Author(s): Montserrat Fuentes*+
Companies: North Carolina State University
Address: Dept. of Statistics, Raleigh, NC, 27695-0001,
Keywords: spatial process ; separability ; stationarity ; air quality ; spectral analysis ; space-time modeling
Abstract:

Most applications in spatial statistics involve spatial temporal modeling. Many of the problems of space and time modeling can be overcome by using separable processes. This subclass of spatial temporal processes has several advantages, including rapid fitting and simple extensions of many techniques developed and successfully used in time series and classical geostatistics. In particular, a major advantage of these processes is that the covariance matrix for a realization can be expressed as the Kronecker product of two smaller matrices that arise separately from the temporal and purely spatial processes, and hence its determinant and inverse are easily determinable. However, these separable models are not always appropriate. We present here a formal test for separability and new nonseparable models for spatial-temporal processes. We apply the statistical methods proposed here to study the separability of spatial temporal air pollution data provided by EPA.

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