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

Yu Yu Linke; I. S. Borisov

doi:10.1016/j.spl.2016.09.022

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

Yu Yu Linke, I. S. Borisov

Кафедра теории вероятностей и математической статистики ММФ

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

7 Цитирования (Scopus)

Аннотация

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.

Язык оригинала	английский
Страницы (с-по)	87-94
Число страниц	8
Журнал	Statistics and Probability Letters
Том	120
DOI	https://doi.org/10.1016/j.spl.2016.09.022
Состояние	Опубликовано - 1 янв 2017

Доступ к документу

10.1016/j.spl.2016.09.022

Link to publication in Scopus

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abstract = "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.",

keywords = "Asymptotic normality, Initial estimator, Nonlinear regression, One-step M-estimator, α-consistency, LINEAR-REGRESSION, alpha(n)-consistency",

author = "Linke, {Yu Yu} and Borisov, {I. S.}",

year = "2017",

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Constructing initial estimators in one-step estimation procedures of nonlinear regression. / Linke, Yu Yu ; Borisov, I. S.

В: Statistics and Probability Letters, Том 120, 01.01.2017, стр. 87-94.

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

TY - JOUR

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AU - Borisov, I. S.

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AB - 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.

KW - Asymptotic normality

KW - Initial estimator

KW - Nonlinear regression

KW - One-step M-estimator

KW - α-consistency

KW - LINEAR-REGRESSION

KW - alpha(n)-consistency

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JO - Statistics and Probability Letters

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