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Sib. Èlektron. Mat. Izv., 2013, Volume 10, Pages 627–640 (Mi semr455)  

This article is cited in 1 scientific paper (total in 1 paper)

Probability theory and mathematical statistics

On asymptotics of the distribution of a two-step statistical estimator of a one-dimensional parameter

Yu. Yu. Linkeab, A. I. Sakhanenkoab

a Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk
b Novosibirsk State University

Abstract: The authors' approach to study two-step estimators of one-dimensional unknown parameters is extended to a wider classes of the first- and second-step estimators which include well known M-estimators. Under general restrictions necessary and sufficient conditions are found for the normalized difference between the second-step estimator and the unknown parameter to converge weakly to an arbitrary distribution.

Keywords: two-step estimators, impovement of statistical estimators, limit distribution, asymptotical normality, M-estimators, regression.

Full text: PDF file (542 kB)
References: PDF file   HTML file
UDC: 519.23
MSC: 62F12
Received October 3, 2013, published November 8, 2013

Citation: Yu. Yu. Linke, A. I. Sakhanenko, “On asymptotics of the distribution of a two-step statistical estimator of a one-dimensional parameter”, Sib. Èlektron. Mat. Izv., 10 (2013), 627–640

Citation in format AMSBIB
\Bibitem{LinSak13}
\by Yu.~Yu.~Linke, A.~I.~Sakhanenko
\paper On asymptotics of the distribution of a two-step statistical estimator of a one-dimensional parameter
\jour Sib. \`Elektron. Mat. Izv.
\yr 2013
\vol 10
\pages 627--640
\mathnet{http://mi.mathnet.ru/semr455}


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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. Yu. Yu. Linke, “Two-step estimation in heteroscedastic linear regression model”, J. Math. Sci., 231:2 (2018), 206–217  mathnet  crossref  crossref
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