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Teoriya Veroyatnostei i ee Primeneniya, 1967, Volume 12, Issue 4, Pages 735–741 (Mi tvp762)  

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

Short Communications

On the estimation theory of the scale parameter

A. M. Kagan, A. L. Rukhin

Leningrad
Full-text PDF (391 kB) Citations (4)
Abstract: The problem of estimating of the scale parameter $\sigma$ based on independent samples from the population with d.f. $F(x/\sigma)$ is considered. Under the condition (10) the following results are proved (Theorems 1 and 2). The estimator $c^\circ_n\bar x$ of $\sigma$ is admissible in the class of all estimators (or $\alpha_1^{-1}\bar x$ is admissible in the class of unbiased estimators) for any two values $n=n_1$, $n=n_2$, $n_2>n_1\ge3$, of the sample size if and only if $F(x)$ is either the degenerate d.f. or the d.f. of the Gamma-distribution.
Received: 09.08.1966
English version:
Theory of Probability and its Applications, 1967, Volume 12, Issue 4, Pages 672–678
DOI: https://doi.org/10.1137/1112083
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. M. Kagan, A. L. Rukhin, “On the estimation theory of the scale parameter”, Teor. Veroyatnost. i Primenen., 12:4 (1967), 735–741; Theory Probab. Appl., 12:4 (1967), 672–678
Citation in format AMSBIB
\Bibitem{KagRuk67}
\by A.~M.~Kagan, A.~L.~Rukhin
\paper On the estimation theory of the scale parameter
\jour Teor. Veroyatnost. i Primenen.
\yr 1967
\vol 12
\issue 4
\pages 735--741
\mathnet{http://mi.mathnet.ru/tvp762}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=221632}
\zmath{https://zbmath.org/?q=an:0283.62041}
\transl
\jour Theory Probab. Appl.
\yr 1967
\vol 12
\issue 4
\pages 672--678
\crossref{https://doi.org/10.1137/1112083}
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  • https://www.mathnet.ru/eng/tvp/v12/i4/p735
  • 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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