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Abstract Details
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Activity Number:
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102
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Type:
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Invited
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Date/Time:
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Monday, August 1, 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 - #300808 |
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Title:
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Analysis of Massive Data Set Through Compactly Supported Covariance Functions
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Author(s):
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Emilio Porcu*+
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Companies:
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University Castilla La Mancha
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Address:
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, , ,
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Keywords:
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Abstract:
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We propose new classes of covariance functions for vector-valued random fields having the additional feature of being compactly supported, which is desirable for practitioners working on massive spatial data sets. In particular, we propose compactly supported matrix-valued mappings generated by the Wu class of covariance functions as well as its generalizations to the so-called Buhmann and Gneiting-Wendland classes. An application to Pacific Ocean temperature and pressure data, as well as a simulation study, illustrate the features of such models.
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