Consistency of the least median of squares estimator in nonlinear regression

Arnold J. Stromberg

doi:10.1080/03610929508831597

Consistency of the least median of squares estimator in nonlinear regression

Arnold J. Stromberg

Dr. Bing Zhang Department of Statistics

Producción científica: Article › revisión exhaustiva

8 Citas (Scopus)

Resumen

Recent research by Sakata and White (1995) presents the consistency and asymptotic normality of S-estimators in nonlinear regression. It is well known from research in linear regression that it is important to use a consistent high breakdown estimator as an initial estimate when computing an S-estimate. This paper presents the proof of the weak consistency of the least median of squares estimator in a nonlinear regression setting, thus suggesting that it is a reasonable choice for the starting value for computing S-estimates in nonlinear regression.

Idioma original	English
Páginas (desde-hasta)	1971-1984
Número de páginas	14
Publicación	Communications in Statistics - Theory and Methods
Volumen	24
N.º	8
DOI	https://doi.org/10.1080/03610929508831597
Estado	Published - ene 1 1995

Nota bibliográfica

Funding Information:
ACKNOWLEDGEMENTS This paper is a revision of a chapter of the authors Ph,D. dissertation from the University of North Carolina at Chapel ill. The author gratefully acknowledges the assistance of his advisor, Dawd Ruppert. lor this research was provided by KSF grant DMS-9204380 and NSA grant DA-904-92-H-3077.

Financiación

ACKNOWLEDGEMENTS This paper is a revision of a chapter of the authors Ph,D. dissertation from the University of North Carolina at Chapel ill. The author gratefully acknowledges the assistance of his advisor, Dawd Ruppert. lor this research was provided by KSF grant DMS-9204380 and NSA grant DA-904-92-H-3077.

Financiadores	Número del financiador
KSF	DMS-9204380
National Security Agency	DA-904-92-H-3077

ASJC Scopus subject areas

Statistics and Probability

Acceder al documento

10.1080/03610929508831597

Otros archivos y enlaces

Citar esto

@article{37e6b436d3bf4e6dabb6831389977277,

title = "Consistency of the least median of squares estimator in nonlinear regression",

abstract = "Recent research by Sakata and White (1995) presents the consistency and asymptotic normality of S-estimators in nonlinear regression. It is well known from research in linear regression that it is important to use a consistent high breakdown estimator as an initial estimate when computing an S-estimate. This paper presents the proof of the weak consistency of the least median of squares estimator in a nonlinear regression setting, thus suggesting that it is a reasonable choice for the starting value for computing S-estimates in nonlinear regression.",

keywords = "robust estimation",

author = "Stromberg, \{Arnold J.\}",

note = "Funding Information: ACKNOWLEDGEMENTS This paper is a revision of a chapter of the authors Ph,D. dissertation from the University of North Carolina at Chapel ill. The author gratefully acknowledges the assistance of his advisor, Dawd Ruppert. lor this research was provided by KSF grant DMS-9204380 and NSA grant DA-904-92-H-3077.",

year = "1995",

month = jan,

day = "1",

doi = "10.1080/03610929508831597",

language = "English",

volume = "24",

pages = "1971--1984",

number = "8",

}

TY - JOUR

T1 - Consistency of the least median of squares estimator in nonlinear regression

AU - Stromberg, Arnold J.

N1 - Funding Information: ACKNOWLEDGEMENTS This paper is a revision of a chapter of the authors Ph,D. dissertation from the University of North Carolina at Chapel ill. The author gratefully acknowledges the assistance of his advisor, Dawd Ruppert. lor this research was provided by KSF grant DMS-9204380 and NSA grant DA-904-92-H-3077.

PY - 1995/1/1

Y1 - 1995/1/1

N2 - Recent research by Sakata and White (1995) presents the consistency and asymptotic normality of S-estimators in nonlinear regression. It is well known from research in linear regression that it is important to use a consistent high breakdown estimator as an initial estimate when computing an S-estimate. This paper presents the proof of the weak consistency of the least median of squares estimator in a nonlinear regression setting, thus suggesting that it is a reasonable choice for the starting value for computing S-estimates in nonlinear regression.

AB - Recent research by Sakata and White (1995) presents the consistency and asymptotic normality of S-estimators in nonlinear regression. It is well known from research in linear regression that it is important to use a consistent high breakdown estimator as an initial estimate when computing an S-estimate. This paper presents the proof of the weak consistency of the least median of squares estimator in a nonlinear regression setting, thus suggesting that it is a reasonable choice for the starting value for computing S-estimates in nonlinear regression.

KW - robust estimation

UR - https://www.scopus.com/pages/publications/84963146401

UR - https://www.scopus.com/pages/publications/84963146401#tab=citedBy

U2 - 10.1080/03610929508831597

DO - 10.1080/03610929508831597

M3 - Article

AN - SCOPUS:84963146401

SN - 0361-0926

VL - 24

SP - 1971

EP - 1984

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 8

ER -

Consistency of the least median of squares estimator in nonlinear regression

Resumen

Nota bibliográfica

Financiación

ASJC Scopus subject areas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto