Constructing initial estimators in one-step estimation procedures of nonlinear regression

Constructing initial estimators in one-step estimation procedures of nonlinear regression Full article

Journal

Statistics and Probability Letters
ISSN: 0167-7152

Output data

Year: 2017, Volume: 120, Pages: 87-94 Pages count : 8 DOI: 10.1016/j.spl.2016.09.022

Tags

Asymptotic normality; Initial estimator; Nonlinear regression; One-step M-estimator; αn-consistency

Authors

Linke Y.Y. ^1,2 , Borisov I.S. ^1,2

Affiliations

1	Sobolev Institute of Mathematics, Novosibirsk State University, Novosibirsk, 630090, Russian Federation
2	Novosibirsk State University

We discuss an approach to construct explicitly calculable consistent estimators for parameters of some nonlinear regression models. The estimators of such a kind can be used as initial estimators in one-step estimation procedures for unknown parameters of these models. © 2016 Elsevier B.V.

Linke Y.Y. , Borisov I.S.
Constructing initial estimators in one-step estimation procedures of nonlinear regression
Statistics and Probability Letters. 2017. V.120. P.87-94. DOI: 10.1016/j.spl.2016.09.022 WOS Scopus OpenAlex

Web of science:	WOS:000388781800011
Scopus:	2-s2.0-84992522070
OpenAlex:	W2528214842

DB	Citing
Scopus	16
OpenAlex	20
Web of science	12