Asymptotic normality of one-step M-estimators based on non-identically distributed observations

Yuliana Yu Linke

doi:10.1016/j.spl.2017.05.020

Asymptotic normality of one-step M-estimators based on non-identically distributed observations

Yuliana Yu Linke

Кафедра теории вероятностей и математической статистики ММФ

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

4 Цитирования (Scopus)

Аннотация

We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.

Язык оригинала	английский
Страницы (с-по)	216-221
Число страниц	6
Журнал	Statistics and Probability Letters
Том	129
DOI	https://doi.org/10.1016/j.spl.2017.05.020
Состояние	Опубликовано - 1 окт 2017

Доступ к документу

10.1016/j.spl.2017.05.020

Другие файлы и ссылки

Link to publication in Scopus

Fingerprint

Подробные сведения о темах исследования «Asymptotic normality of one-step M-estimators based on non-identically distributed observations». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать

@article{8b7287c669d2444ea02f9fe3ce0903e9,

title = "Asymptotic normality of one-step M-estimators based on non-identically distributed observations",

abstract = "We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.",

keywords = "Initial estimator, Nonlinear regression, One-step M-estimator",

author = "Linke, {Yuliana Yu}",

year = "2017",

month = oct,

day = "1",

doi = "10.1016/j.spl.2017.05.020",

language = "English",

volume = "129",

pages = "216--221",

journal = "Statistics and Probability Letters",

issn = "0167-7152",

publisher = "Elsevier Science B.V.",

}

Asymptotic normality of one-step M-estimators based on non-identically distributed observations. / Linke, Yuliana Yu.

В: Statistics and Probability Letters, Том 129, 01.10.2017, стр. 216-221.

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

TY - JOUR

T1 - Asymptotic normality of one-step M-estimators based on non-identically distributed observations

AU - Linke, Yuliana Yu

PY - 2017/10/1

Y1 - 2017/10/1

N2 - We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.

AB - We find general conditions for asymptotic normality of two types of one-step M-estimators based on independent not necessarily identically distributed observations. As an application, we consider some examples of one-step approximation of quasi-likelihood estimators in nonlinear regression.

KW - Initial estimator

KW - Nonlinear regression

KW - One-step M-estimator

UR - http://www.scopus.com/inward/record.url?scp=85020986354&partnerID=8YFLogxK

U2 - 10.1016/j.spl.2017.05.020

DO - 10.1016/j.spl.2017.05.020

M3 - Article

AN - SCOPUS:85020986354

VL - 129

SP - 216

EP - 221

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

ER -