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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.

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Harvard

Linke, YY 2017, 'Asymptotic normality of one-step M-estimators based on non-identically distributed observations', Statistics and Probability Letters, Том. 129, стр. 216-221. https://doi.org/10.1016/j.spl.2017.05.020

APA

Linke, Y. Y. (2017). Asymptotic normality of one-step M-estimators based on non-identically distributed observations. Statistics and Probability Letters, 129, 216-221. https://doi.org/10.1016/j.spl.2017.05.020

Vancouver

Linke YY. Asymptotic normality of one-step M-estimators based on non-identically distributed observations. Statistics and Probability Letters. 2017 окт. 1;129:216-221. doi: 10.1016/j.spl.2017.05.020

Author

Linke, Yuliana Yu. / Asymptotic normality of one-step M-estimators based on non-identically distributed observations. в: Statistics and Probability Letters. 2017 ; Том 129. стр. 216-221.

BibTeX

@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.",

}

RIS

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 -

ID: 9048672