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

6 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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Цитировать

Linke, Y. Y., & Borisov, I. S. (2017). Constructing initial estimators in one-step estimation procedures of nonlinear regression. Statistics and Probability Letters, 120, 87-94. https://doi.org/10.1016/j.spl.2016.09.022

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

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KW - One-step M-estimator

KW - α-consistency

KW - LINEAR-REGRESSION

KW - alpha(n)-consistency

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