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dc.contributor.authorAlsultan, Rehab
dc.contributor.authorMa, Chunsheng
dc.identifier.citationR. Alsultan and C. Ma. 2019. K-differenced vector random fields. Theory of Probability & Its Applications, 2019 63:3, 393-407en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractA thin-tailed vector random field, referred to as a K-differenced vector random field, is introduced. Its finite-dimensional densities are the differences of two Besse! functions of second order, whenever they exist, and its finite-dimensional characteristic functions have simple closed forms as the differences of two power functions or logarithm functions. Its finite-dimensional distributions have thin tails, even thinner than those of a Gaussian one, and it reduces to a Linnik or Laplace vector random field in a limiting case. As one of its most valuable properties, a K-differencexl vector random field is characterized by its mean and covariance matrix functions just like a Gaussian one. Some covariance matrix structures are constructed in this paper for not only the K-differenced vector random field, but also for other second-order elliptically contoured vector random fields. Properties of the multivariate K-differenced distribution are also studied.en_US
dc.publisherSIAM Publ.en_US
dc.relation.ispartofseriesTheory of Probability & Its Applications;v.63:no.3
dc.subjectCovariance matrix functionen_US
dc.subjectCross covarianceen_US
dc.subjectDirect covarianceen_US
dc.subjectElliptically contoured random fielden_US
dc.subjectGaussian random fielden_US
dc.subjectK-differenced distributionen_US
dc.subjectSpherically invariant random fielden_US
dc.titleK-differenced vector random fieldsen_US
dc.rights.holder© 2019, Society for Industrial and Applied Mathematicsen_US

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