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JOURNALS // Teoriya Veroyatnostei i ee Primeneniya // Archive

Teor. Veroyatnost. i Primenen., 2018 Volume 63, Issue 1, Pages 29–56 (Mi tvp5155)

This article is cited in 18 papers

Constructing explicit estimators in nonlinear regression problems

Yu. Yu. Linkeab, I. S. Borisovab

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

Abstract: In the paper, we propose a general approach to constructing explicit consistent estimators for some classes of nonlinear regression models. These estimators can be used as initial ones in one-step estimation procedures capable of delivering, in a sense, optimal estimators in an explicit form.

Keywords: nonlinear regression, explicit estimator, $\alpha_n$-consistency, asymptotic normality, one-step estimator, initial estimator.

Received: 24.02.2016
Accepted: 22.05.2017

DOI: 10.4213/tvp5155


 English version:
Theory of Probability and its Applications, 2018, 63:1, 22–44

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