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Conditions of Asymptotic Normality of One-Step M-Estimators. / Linke, Yu Yu; Sakhanenko, A. I.

In: Journal of Mathematical Sciences (United States), Vol. 230, No. 1, 01.04.2018, p. 95-111.

Research output: Contribution to journal › Article › peer-review

Harvard

Linke, YY & Sakhanenko, AI 2018, 'Conditions of Asymptotic Normality of One-Step M-Estimators', Journal of Mathematical Sciences (United States), vol. 230, no. 1, pp. 95-111. https://doi.org/10.1007/s10958-018-3730-3

APA

Linke, Y. Y., & Sakhanenko, A. I. (2018). Conditions of Asymptotic Normality of One-Step M-Estimators. Journal of Mathematical Sciences (United States), 230(1), 95-111. https://doi.org/10.1007/s10958-018-3730-3

Vancouver

Linke YY, Sakhanenko AI. Conditions of Asymptotic Normality of One-Step M-Estimators. Journal of Mathematical Sciences (United States). 2018 Apr 1;230(1):95-111. doi: 10.1007/s10958-018-3730-3

Author

Linke, Yu Yu ; Sakhanenko, A. I. / Conditions of Asymptotic Normality of One-Step M-Estimators. In: Journal of Mathematical Sciences (United States). 2018 ; Vol. 230, No. 1. pp. 95-111.

BibTeX

@article{0a78735cf7044049ac88d9b735729fa5,
title = "Conditions of Asymptotic Normality of One-Step M-Estimators",
abstract = "In the case of independent identically distributed observations, we study the asymptotic properties of one-step M-estimators served as explicit approximations of consistent M-estimators. We find rather general conditions for the asymptotic normality of one-step M-estimators. We consider Fisher{\textquoteright}s approximations of consistent maximum likelihood estimators and find general conditions guaranteeing the asymptotic normality of the Fisher estimators even in the case where maximum likelihood estimators do not necessarily exist or are not necessarily consistent.",
author = "Linke, {Yu Yu} and Sakhanenko, {A. I.}",
year = "2018",
month = apr,
day = "1",
doi = "10.1007/s10958-018-3730-3",
language = "English",
volume = "230",
pages = "95--111",
journal = "Journal of Mathematical Sciences (United States)",
issn = "1072-3374",
publisher = "Springer Nature",
number = "1",

}

RIS

TY - JOUR

T1 - Conditions of Asymptotic Normality of One-Step M-Estimators

AU - Linke, Yu Yu

AU - Sakhanenko, A. I.

PY - 2018/4/1

Y1 - 2018/4/1

N2 - In the case of independent identically distributed observations, we study the asymptotic properties of one-step M-estimators served as explicit approximations of consistent M-estimators. We find rather general conditions for the asymptotic normality of one-step M-estimators. We consider Fisher’s approximations of consistent maximum likelihood estimators and find general conditions guaranteeing the asymptotic normality of the Fisher estimators even in the case where maximum likelihood estimators do not necessarily exist or are not necessarily consistent.

AB - In the case of independent identically distributed observations, we study the asymptotic properties of one-step M-estimators served as explicit approximations of consistent M-estimators. We find rather general conditions for the asymptotic normality of one-step M-estimators. We consider Fisher’s approximations of consistent maximum likelihood estimators and find general conditions guaranteeing the asymptotic normality of the Fisher estimators even in the case where maximum likelihood estimators do not necessarily exist or are not necessarily consistent.

UR - http://www.scopus.com/inward/record.url?scp=85042544553&partnerID=8YFLogxK

U2 - 10.1007/s10958-018-3730-3

DO - 10.1007/s10958-018-3730-3

M3 - Article

AN - SCOPUS:85042544553

VL - 230

SP - 95

EP - 111

JO - Journal of Mathematical Sciences (United States)

JF - Journal of Mathematical Sciences (United States)

SN - 1072-3374

IS - 1

ER -

ID: 10453036