Constructing explicit estimators in nonlinear regression problems Full article
| Journal |
Theory of Probability and its Applications
ISSN: 0040-585X , E-ISSN: 1095-7219 |
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| Output data | Year: 2018, Volume: 63, Number: 1, Pages: 22-44 Pages count : 23 DOI: 10.1137/S0040585X97T988897 | ||||
| Tags | Asymptotic normality; Explicit estimator; Initial estimator; Nonlinear regression; One-step estimator; α n -consistency | ||||
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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. © 2018 Society for Industrial and Applied Mathematics.
Cite:
Linke Y.Y.
, Borisov I.S.
Constructing explicit estimators in nonlinear regression problems
Theory of Probability and its Applications. 2018. V.63. N1. P.22-44. DOI: 10.1137/S0040585X97T988897 WOS Scopus OpenAlex
Constructing explicit estimators in nonlinear regression problems
Theory of Probability and its Applications. 2018. V.63. N1. P.22-44. DOI: 10.1137/S0040585X97T988897 WOS Scopus OpenAlex
Identifiers:
| Web of science: | WOS:000448195400002 |
| Scopus: | 2-s2.0-85057338140 |
| OpenAlex: | W2898427130 |