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Teoriya Veroyatnostei i ee Primeneniya, 1995, Volume 40, Issue 1, Pages 205–213 (Mi tvp3438)  

This article is cited in 8 scientific papers (total in 8 papers)

Short Communications

Linear estimators and radonifying operators

H. Luschgy

Institut für Mathematische Statistik, Universität Münster, Münster, Federal Republic of Germany
Full-text PDF (543 kB) Citations (8)
Abstract: We consider the problem of estimating a signal $Y$ with values in a Banach space based on the observation $X$ with values in another Banach space given their joint Gaussian distribution. Linear estimators are denned to be measurable linear transformations. A characterization of measurable linear transformations with respect to a Gaussian measure by radonifying operators is established. The Bayes estimator $\mathbf{E}(Y|X)$ is shown to be a measurable linear transformation and the associated radonifying operator is derived.
Keywords: radonifying operator, measurable linear transformation, conditional Gaussian distribution.
Received: 05.02.1992
English version:
Theory of Probability and its Applications, 1995, Volume 40, Issue 1, Pages 167–175
DOI: https://doi.org/10.1137/1140017
Bibliographic databases:
Document Type: Article
Language: English
Citation: H. Luschgy, “Linear estimators and radonifying operators”, Teor. Veroyatnost. i Primenen., 40:1 (1995), 205–213; Theory Probab. Appl., 40:1 (1995), 167–175
Citation in format AMSBIB
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\by H.~Luschgy
\paper Linear estimators and radonifying operators
\jour Teor. Veroyatnost. i Primenen.
\yr 1995
\vol 40
\issue 1
\pages 205--213
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\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=1346746}
\zmath{https://zbmath.org/?q=an:0839.62089}
\transl
\jour Theory Probab. Appl.
\yr 1995
\vol 40
\issue 1
\pages 167--175
\crossref{https://doi.org/10.1137/1140017}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=A1996UH07100017}
Linking options:
  • https://www.mathnet.ru/eng/tvp3438
  • https://www.mathnet.ru/eng/tvp/v40/i1/p205
  • This publication is cited in the following 8 articles:
    1. De-Han Chen, Jingzhi Li, Ye Zhang, “A posterior contraction for Bayesian inverse problems in Banach spaces”, Inverse Problems, 40:4 (2024), 045011  crossref
    2. Alessandra Menafoglio, Davide Pigoli, Piercesare Secchi, Wiley Series in Probability and Statistics, Geostatistical Functional Data Analysis, 2022, 27  crossref
    3. Menafoglio A., Petris G., “Kriging for Hilbert-space valued random fields: The operatorial point of view”, J. Multivar. Anal., 146:SI (2016), 84–94  crossref  mathscinet  zmath  isi  scopus
    4. Florens J.-P., Simoni A., “Regularizing Priors For Linear Inverse Problems”, Economet. Theory, 32:1 (2016), 71–121  crossref  mathscinet  zmath  isi  scopus
    5. JEAN‐PIERRE FLORENS, ANNA SIMONI, “Regularized Posteriors in Linear Ill‐Posed Inverse Problems”, Scandinavian J Statistics, 39:2 (2012), 214  crossref
    6. Sari Lasanen, “Non-Gaussian statistical inverse problems. Part I: Posterior distributions”, IPI, 6:2 (2012), 215  crossref
    7. Andreas Hofinger, Hanna K. Pikkarainen, “Convergence Rates for Linear Inverse Problems in the Presence of an Additive Normal Noise”, Stochastic Analysis and Applications, 27:2 (2009), 240  crossref
    8. Andreas Hofinger, Hanna K Pikkarainen, “Convergence rate for the Bayesian approach to linear inverse problems”, Inverse Problems, 23:6 (2007), 2469  crossref
    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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