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Equivalence of Gaussian measures of multivariate random fields

Lookup NU author(s): Professor Emilio Porcu

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Abstract

Problems related to weather forecast, forest attributes estimation and prediction, disease propagation, among others, are commonly approximated in the framework of multivariate Gaussian random field modeling. This paper deals with the equivalence condition of two zero-mean Gaussian infinite-dimensional vector measures defined on the finite product of separable Hilbert spaces. In particular, sufficient conditions are provided. The results derived are applied to obtain the equivalence of Gaussian measures associated with two stationary zero-mean Gaussian vector random fields. Classical problems related to, for example, asymptotic properties of maximum likelihood vector Gaussian random field parameter estimators from tapered multivariate covariance functions, often arising in Multivariate Geostatistics, can be solved as direct application of the results derived.

Publication metadata

Author(s): Ruiz-Medina MD, Porcu E

Publication type: Article

Publication status: Published

Journal: Stochastic Environmental Research and Risk Assessment

Year: 2015

Volume: 29

Issue: 2

Pages: 325-334

Print publication date: 01/02/2015

Online publication date: 08/08/2014

Acceptance date: 08/07/2014

ISSN (print): 1436-3240

ISSN (electronic): 1436-3259

Publisher: Springer

URL: https://doi.org/10.1007/s00477-014-0926-z

DOI: 10.1007/s00477-014-0926-z

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