JSM 2004 - Toronto

Abstract #300224

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Activity Number: 208
Type: Invited
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #300224
Title: Space-time Parameter Estimation Using Approximate Likelihoods
Author(s): Jonathan R. Stroud*+
Companies: Wharton School, University of Pennsylvania
Address: Statistics Dept., Philadephia, PA, 19102,
Keywords: likelihood approximation ; Kalman filter ; parameter estimation ; model selection
Abstract:

In a recent paper by Stein, Chi and Welty (2003), new methods were proposed for approximating the likelihood for a spatial Gaussian process. We extend their method to the spatio-temporal setting and show how this can be used to perform parameter estimation and model selection in a large class of linear state-space models. We illustrate the method through an example involving remote sensing.

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Revised March 2004