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DIFFERENTIAL REPRESENTATION AND MARKOV PROPERTY OF GENERALIZED RANDOM FIELDS 

Authors: V. V. Anh a;  M. D. Ruiz-Medina b; J. M. Angulo b
Affiliations:   a Centre in Statistical Science and Industrial Mathematics, Queensland University of Technology, Brisbane, QLD, Australia
b Department of Statistics & Operations Research, University of Granada, Granada, Spain
DOI: 10.1081/SAP-100002098
Publication Frequency: 6 issues per year
Published in: journal Stochastic Analysis and Applications, Volume 19, Issue 4 June 2001 , pages 481 - 498
Formats available: HTML (English) : PDF (English)
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Abstract

Using the geometric properties of Sobolev spaces of integer order and a duality condition, the covariance operators of a generalized random field and its dual can be factorized. Via this covariance factorization, a representation of the generalized random field is obtained as a stochastic equation driven by generalized white noise. This stochastic equation becomes a differential equation under the orthogonality of the dual random field. The solution to this equation satisfies the weak-sense Markov property of integer order. Furthermore, such a solution admits a mean-square series expansion in terms of the eigenfunctions associated with the pure point spectrum of the corresponding covariance operator. From this representation, the relationship between the covariance function and the Green function, associated with the corresponding deterministic problem, in the ordinary case, is derived under suitable conditions.
Keywords: Covariance factorization; Markov representation; Generalized random field; Generalized white noise
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