Mixture-based modeling for space-time data

An overview of spatio‐temporal covariance functions built through mixtures is presented in this paper. We highlight the potentiality of mixture modeling for the construction of nonseparable space–time covariances. In particular, we make use of mixed forms (MF), copulas, and completely monotone funct...

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Bibliographic Details
Published inEnvironmetrics (London, Ont.) Vol. 18; no. 3; pp. 285 - 302
Main Authors Porcu, E., Mateu, J.
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.05.2007
Subjects
2000 MATHEMATICS SUBJECT CLASSIFICATION
43A35
60G60
62H11
62M10
62M40
completely monotone functions
copulas
mixed forms
mixture modeling
space-time covariance functions
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ISSN1180-4009
1099-095X
DOI10.1002/env.832

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Summary:An overview of spatio‐temporal covariance functions built through mixtures is presented in this paper. We highlight the potentiality of mixture modeling for the construction of nonseparable space–time covariances. In particular, we make use of mixed forms (MF), copulas, and completely monotone functions as the basic setup representing powerful instruments to build mixture‐based covariance functions. We re‐analyze, by using a particular model of mixtures, the Indian Ocean wind speed data and compare the results with others previously published in the literature. Copyright © 2007 John Wiley & Sons, Ltd.
Bibliography:ArticleID:ENV832
Spanish Ministry of Science and Education - No. MTM2004-06231
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istex:F3F505D719C978AC51BA558767B1B6D583914826
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:1180-4009
1099-095X
DOI:10.1002/env.832