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Siberian Journal of Pure and Applied Mathematics, 2017, Volume 17, Issue 2, Pages 39–51
DOI: https://doi.org/10.17377/PAM.2017.17.204 (Mi vngu437) 		 
Two-step estimation in heteroscedastic linear regression model

Yu. Yu. Linkeab

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.2017.17.204
Abstract: We study the problem of estimating a parameter in some linear heteroscedastic regression model in the case where the regressors consist of all order statistics based on the sample of identically distributed not necessarily independent observations with finite second moment. It is assumed that the random errors depend on the parameter and distributions of the corresponding regressors. We propose a two-step procedure for finding explicit asymptotically normal estimates.
Keywords: linear regression, order statistics, heteroscedastic, asymptotic normality, $\varphi$-mixing, two-step estimators.
Funding agency Grant number
Russian Foundation for Basic Research 14–01–00220_а
Received: 29.11.2015
English version:
Journal of Mathematical Sciences, 2018, Volume 231, Issue 2, Pages 206–217
DOI: https://doi.org/10.1007/s10958-018-3816-y
Document Type: Article
UDC: 519.233.5
Language: Russian
Citation: Yu. Yu. Linke, “Two-step estimation in heteroscedastic linear regression model”, Sib. J. Pure and Appl. Math., 17:2 (2017), 39–51; J. Math. Sci., 231:2 (2018), 206–217
Citation in format AMSBIB
\Bibitem{Lin17}
\by Yu.~Yu.~Linke
\paper Two-step estimation in heteroscedastic linear regression model
\jour Sib. J. Pure and Appl. Math.
\yr 2017
\vol 17
\issue 2
\pages 39--51
\mathnet{http://mi.mathnet.ru/vngu437}
\crossref{https://doi.org/10.17377/PAM.2017.17.204}
\transl
\jour J. Math. Sci.
\yr 2018
\vol 231
\issue 2
\pages 206--217
\crossref{https://doi.org/10.1007/s10958-018-3816-y}
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