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Teoriya Veroyatnostei i ee Primeneniya, 1973, Volume 18, Issue 3, Pages 535–546 (Mi tvp2726)  
This article is cited in 7 scientific papers (total in 8 papers)

On moments of generalized Bayessian estimators and maximum likelihood estimators

I. A. Ibragimova, R. Z. Khas'minskiib

a Leningrad
b Moscow
Full-text PDF (610 kB) Citations (8)
Abstract: The main results of this paper are the Theorems 1 and 2 and in particular, inequali ties (3.2). These theorems consider properties of the Bayessian estimates $\widetilde\theta_n$ for a wide class of a priory densities and cost functions. Precise conditions are formulated in Section 2 (see conditions A$_1$–A$_3$, Б$_1$–Б$_5$). Analogous theorems are proved in Section 7 for the maximum likelihood estimate under some additional conditions.
Received: 16.05.1972
English version:
Theory of Probability and its Applications, 1974, Volume 18, Issue 3, Pages 508–520
DOI: https://doi.org/10.1137/1118065
Bibliographic databases:
Language: Russian
Citation: I. A. Ibragimov, R. Z. Khas'minskii, “On moments of generalized Bayessian estimators and maximum likelihood estimators”, Teor. Veroyatnost. i Primenen., 18:3 (1973), 535–546; Theory Probab. Appl., 18:3 (1974), 508–520
Citation in format AMSBIB
\Bibitem{IbrKha73}
\by I.~A.~Ibragimov, R.~Z.~Khas'minskii
\paper On moments of generalized Bayessian estimators and maximum likelihood estimators
\jour Teor. Veroyatnost. i Primenen.
\yr 1973
\vol 18
\issue 3
\pages 535--546
\mathnet{http://mi.mathnet.ru/tvp2726}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=324821}
\zmath{https://zbmath.org/?q=an:0327.62017}
\transl
\jour Theory Probab. Appl.
\yr 1974
\vol 18
\issue 3
\pages 508--520
\crossref{https://doi.org/10.1137/1118065}
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  • https://www.mathnet.ru/eng/tvp/v18/i3/p535
    • This publication is cited in the following 8 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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