Strong convergence of LAD estimates in a censored regression model

Yixin Fang; Man Jin; Lincheng Zhao

doi:10.1360/03ys0166

Strong convergence of LAD estimates in a censored regression model

Yixin Fang, Man Jin, Lincheng Zhao

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

5 Scopus citations

Abstract

A regression model with a nonnegativity constraint on the dependent variable, known as censored median regression model, is considered. Under some mild conditions, the LAD estimate of the regression coefficient is shown to be strongly consistent. Furthermore, its convergence rate and Bahadur strong representation are also obtained.

Original language	English (US)
Pages (from-to)	155-168
Number of pages	14
Journal	Science in China, Series A: Mathematics
Volume	48
Issue number	2
DOIs	https://doi.org/10.1360/03ys0166
State	Published - Feb 2005
Externally published	Yes

All Science Journal Classification (ASJC) codes

General Mathematics

Keywords

Bahadur representation
Censored regression
Convergence rate
LAD estimator
Strong consistency

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10.1360/03ys0166

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title = "Strong convergence of LAD estimates in a censored regression model",

abstract = "A regression model with a nonnegativity constraint on the dependent variable, known as censored median regression model, is considered. Under some mild conditions, the LAD estimate of the regression coefficient is shown to be strongly consistent. Furthermore, its convergence rate and Bahadur strong representation are also obtained.",

keywords = "Bahadur representation, Censored regression, Convergence rate, LAD estimator, Strong consistency",

author = "Yixin Fang and Man Jin and Lincheng Zhao",

note = "Funding Information: Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 10171094), Ph.D. Program Foundation of the Ministry of Education of China and Special Foundations of the Chinese Academy of Sciences and University of Science and Technology of China.",

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AU - Jin, Man

AU - Zhao, Lincheng

N1 - Funding Information: Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 10171094), Ph.D. Program Foundation of the Ministry of Education of China and Special Foundations of the Chinese Academy of Sciences and University of Science and Technology of China.

PY - 2005/2

Y1 - 2005/2

N2 - A regression model with a nonnegativity constraint on the dependent variable, known as censored median regression model, is considered. Under some mild conditions, the LAD estimate of the regression coefficient is shown to be strongly consistent. Furthermore, its convergence rate and Bahadur strong representation are also obtained.

AB - A regression model with a nonnegativity constraint on the dependent variable, known as censored median regression model, is considered. Under some mild conditions, the LAD estimate of the regression coefficient is shown to be strongly consistent. Furthermore, its convergence rate and Bahadur strong representation are also obtained.

KW - Bahadur representation

KW - Censored regression

KW - Convergence rate

KW - LAD estimator

KW - Strong consistency

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Strong convergence of LAD estimates in a censored regression model

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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