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Teoriya Veroyatnostei i ee Primeneniya, 1982, Volume 27, Issue 2, Pages 388–395 (Mi tvp2369)  
This article is cited in 21 scientific papers (total in 21 papers)

Short Communications

Geometrical approach to the maximum likelihood estimation for infinite-dimensional Gaussian location. I

B. S. Cirel'son

Leningrad
Full-text PDF (559 kB) Citations (21)
Abstract: The MLE for the mean of the infinite-dimensional Gaussian measure with given covariance is studied; we assume that the mean belongs to a given set $V$ and relate the behaviour of MLE with the metric properties of $V$ (the metric is induced by the covariance). For example, a Hölder signal in the white noise admits the MLE if the Hölder exponent is greater than $1/2$ . Some inequalities for the distance between the mean and its MLE are given.
Received: 05.12.1978
English version:
Theory of Probability and its Applications, 1983, Volume 27, Issue 2, Pages 411–418
DOI: https://doi.org/10.1137/1127049
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: B. S. Cirel'son, “Geometrical approach to the maximum likelihood estimation for infinite-dimensional Gaussian location. I”, Teor. Veroyatnost. i Primenen., 27:2 (1982), 388–395; Theory Probab. Appl., 27:2 (1983), 411–418
Citation in format AMSBIB
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\paper Geometrical approach to the maximum likelihood estimation for infinite-dimensional Gaussian location.~I
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\yr 1982
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\issue 2
\pages 388--395
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\transl
\jour Theory Probab. Appl.
\yr 1983
\vol 27
\issue 2
\pages 411--418
\crossref{https://doi.org/10.1137/1127049}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=A1983QN71900025}
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  • https://www.mathnet.ru/eng/tvp/v27/i2/p388
    Cycle of papers
    This publication is cited in the following 21 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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