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Abstract Details
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Activity Number:
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523
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #301303 |
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Title:
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Nonparametric Spatial Low Rank Models
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Author(s):
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Cheng Liu*+ and Hao Zhang
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Companies:
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Purdue University and Purdue University
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Address:
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Department of Statistics, West Lafayette, IN, 47907-2066,
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Keywords:
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EM algorithm ;
Geostatistics ;
Kriging ;
Non-parametric model
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Abstract:
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We propose a non-parametric approach to modeling the spatial covariance function. The non-parametric approach avoids the selection of parametric family of covariance function. We employ the EM algorithm to estimate the covariance function. Our approach is capable of handling large spatial data sets. Some numerical results are shown to compare our approach to some other approaches.
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