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Teoriya Veroyatnostei i ee Primeneniya, 1983, Volume 28, Issue 1, Pages 175–182 (Mi tvp2167)  

This article is cited in 4 scientific papers (total in 4 papers)

Short Communications

On the prediction of a class of random fields

L. I. Piterbarg

Moscow
Full-text PDF (611 kB) Citations (4)
Abstract: We consider a class of random fields which is a generalization of a class of homogeneous random fields with rational spectral density. This class contains Gaussian Markov fields. In the Gaussian case the splitting $\sigma$-algebras for a bounded region with smooth boundary are described. We deduce also an explicit linear prediction formula (based on the observations in the bounded region) for a homogeneous isotropic field with rational spectral density.
Received: 30.01.1980
English version:
Theory of Probability and its Applications, 1984, Volume 28, Issue 1, Pages 184–191
DOI: https://doi.org/10.1137/1128015
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: L. I. Piterbarg, “On the prediction of a class of random fields”, Teor. Veroyatnost. i Primenen., 28:1 (1983), 175–182; Theory Probab. Appl., 28:1 (1984), 184–191
Citation in format AMSBIB
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\by L.~I.~Piterbarg
\paper On the prediction of a~class of random fields
\jour Teor. Veroyatnost. i Primenen.
\yr 1983
\vol 28
\issue 1
\pages 175--182
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\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=691479}
\zmath{https://zbmath.org/?q=an:0568.60054}
\transl
\jour Theory Probab. Appl.
\yr 1984
\vol 28
\issue 1
\pages 184--191
\crossref{https://doi.org/10.1137/1128015}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=A1984SL53600015}
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  • https://www.mathnet.ru/eng/tvp/v28/i1/p175
  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Теория вероятностей и ее применения Theory of Probability and its Applications
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