Abstract #302071

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JSM 2003 Abstract #302071
Activity Number: 236
Type: Topic Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract - #302071
Title: Monte Carlo Filtering for High-Dimensional Space-Time Models
Author(s): Jonathan Reuben Stroud*+ and Michael L. Stein
Companies: University of Pennsylvania and University of Chicago
Address: 1500 Locust St., Philadelphia, PA, 19102-4329,
Keywords: particle filtering ; Monte Carlo methods ; spatio-temporal models ; Markov random field ; variogram ; hydrodynamic model
Abstract:

We propose a particle filtering method for high-dimensional space-time models. We focus on models with nonlinear dynamics and data observed on a regular lattice. We describe computational algorithms for two types of error structures: spatial variogram models and Markov random fields. To illustrate the method we consider the problem of hydrodynamic modeling in Lake Michigan.

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