This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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118
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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Abstract - #308133 |
Title:
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Cross-Covariance Functions for Multivariate Random Fields Based on Latent Dimensions
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Author(s):
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Marc Genton*+ and Tatiyana Apanasovich
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Companies:
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Texas A&M University and Thomas Jefferson University
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Address:
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Department of Statistics, College Station, TX, 77843,
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Keywords:
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Asymmetry ;
Linear model of coregionalization ;
Nonseparability ;
Positive definiteness ;
Space and Time ;
Stationarity
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Abstract:
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The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable, and computationally feasible classes of cross-covariance functions in closed form. We focus on spatio-temporal cross-covariance functions that can be nonseparable, asymmetric, and can have different covariance structures, for instance different smoothness parameters, in each component. We discuss estimation of these models and perform a small simulation study to demonstrate our approach. We illustrate our methodology on a trivariate spatio-temporal pollution dataset from California and demonstrate that our cross-covariance performs better than other competing models.
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