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Abstract Details
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Activity Number:
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313
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 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 - #302886 |
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Title:
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Bayesian Estimation of Multivariate Matern Covariance Parameters
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Author(s):
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Bonnie B. Terry*+ and Jane Harvill
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Companies:
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Baylor University and Baylor University
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Address:
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101 North 1st street, Cranfills Gap, TX, 76637,
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Keywords:
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Multivariate geostatistics ;
Matern covariance function ;
Bayesian estimation
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Abstract:
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Covariance modeling and estimation is key to spatial prediction methods. Univariate techniques have been widely studied and implemented. Often, however, significant gains may be realized from simultaneously modeling the spatial dependance structure of two or more attributes. Gneiting, et al. (2010) develop a valid Matern cross-covariance function for multivariate Gaussian random fields. We employ Bayesian methodology to parameter estimation for the multivariate Matern model.
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