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Siberian Journal of Pure and Applied Mathematics, 2016, Volume 16, Issue 4, Pages 46–64
DOI: https://doi.org/10.17377/PAM.2016.16.406 (Mi vngu421) 		 
This article is cited in 2 scientific papers (total in 2 papers)

Conditions of asymptotic normality of one-step $M$-estimators

Yu. Yu. Linkeab, A. I. Sakhanenkoab

a Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk
b Novosibirsk State University
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DOI: https://doi.org/10.17377/PAM.2016.16.406
Abstract: In the case of independent identically distributed observations we study asymptotic behavior of one-step $M$-estimators which are explicit approximations to the corresponding consistent $M$-estimators. In particulary, we find quite general conditions for asymptotic normality of one-step $M$-estimators under consideration. As a consequence, we consider Fisher's one-step approximations to consistent maximum likelihood estimators.
Keywords: one-step $M$-estimators, asymptotic normality, $M$-estimators, maximum likelihood estimators, Newton method, preliminary estimators.
Funding agency Grant number
Russian Foundation for Basic Research 14-01-00220_а
Received: 25.02.2016
English version:
Journal of Mathematical Sciences, 2018, Volume 230, Issue 1, Pages 95–111
DOI: https://doi.org/10.1007/s10958-018-3730-3
Document Type: Article
UDC: 519.233.2
Language: Russian
Citation: Yu. Yu. Linke, A. I. Sakhanenko, “Conditions of asymptotic normality of one-step $M$-estimators”, Sib. J. Pure and Appl. Math., 16:4 (2016), 46–64; J. Math. Sci., 230:1 (2018), 95–111
Citation in format AMSBIB
\Bibitem{LinSak16}
\by Yu.~Yu.~Linke, A.~I.~Sakhanenko
\paper Conditions of asymptotic normality of one-step $M$-estimators
\jour Sib. J. Pure and Appl. Math.
\yr 2016
\vol 16
\issue 4
\pages 46--64
\mathnet{http://mi.mathnet.ru/vngu421}
\crossref{https://doi.org/10.17377/PAM.2016.16.406}
\transl
\jour J. Math. Sci.
\yr 2018
\vol 230
\issue 1
\pages 95--111
\crossref{https://doi.org/10.1007/s10958-018-3730-3}
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