Shrinkage estimator of regression model under asymmetric loss

Zahirul Hoque; Jacek Wesolowski; Shahadut Hossain

doi:10.1080/03610926.2017.1397169

Shrinkage estimator of regression model under asymmetric loss

Zahirul Hoque, Jacek Wesolowski, Shahadut Hossain

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

5 Citations (Scopus)

Abstract

This article investigates the performance of the shrinkage estimator (SE) of the parameters of a simple linear regression model under the LINEX loss criterion. The risk function of the estimator under the asymmetric LINEX loss is derived and analyzed. The moment-generating functions and the first two moments of the estimators are also obtained. The risks of the SE have been compared numerically with that of pre-test and least-square estimators (LSEs) under the LINEX loss criterion. The numerical comparison reveals that under certain conditions the LSE is inadmissible, and the SE is the best among the three estimators.

Original language	English
Pages (from-to)	5547-5557
Number of pages	11
Journal	Communications in Statistics - Theory and Methods
Volume	47
Issue number	22
DOIs	https://doi.org/10.1080/03610926.2017.1397169
Publication status	Published - Nov 17 2018

Keywords

LINEX loss and risk function
Linear regression
Normal error
Pre-test estimator
Shrinkage estimator

ASJC Scopus subject areas

Statistics and Probability

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10.1080/03610926.2017.1397169

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title = "Shrinkage estimator of regression model under asymmetric loss",

abstract = "This article investigates the performance of the shrinkage estimator (SE) of the parameters of a simple linear regression model under the LINEX loss criterion. The risk function of the estimator under the asymmetric LINEX loss is derived and analyzed. The moment-generating functions and the first two moments of the estimators are also obtained. The risks of the SE have been compared numerically with that of pre-test and least-square estimators (LSEs) under the LINEX loss criterion. The numerical comparison reveals that under certain conditions the LSE is inadmissible, and the SE is the best among the three estimators.",

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T1 - Shrinkage estimator of regression model under asymmetric loss

AU - Hoque, Zahirul

AU - Wesolowski, Jacek

AU - Hossain, Shahadut

PY - 2018/11/17

Y1 - 2018/11/17

N2 - This article investigates the performance of the shrinkage estimator (SE) of the parameters of a simple linear regression model under the LINEX loss criterion. The risk function of the estimator under the asymmetric LINEX loss is derived and analyzed. The moment-generating functions and the first two moments of the estimators are also obtained. The risks of the SE have been compared numerically with that of pre-test and least-square estimators (LSEs) under the LINEX loss criterion. The numerical comparison reveals that under certain conditions the LSE is inadmissible, and the SE is the best among the three estimators.

AB - This article investigates the performance of the shrinkage estimator (SE) of the parameters of a simple linear regression model under the LINEX loss criterion. The risk function of the estimator under the asymmetric LINEX loss is derived and analyzed. The moment-generating functions and the first two moments of the estimators are also obtained. The risks of the SE have been compared numerically with that of pre-test and least-square estimators (LSEs) under the LINEX loss criterion. The numerical comparison reveals that under certain conditions the LSE is inadmissible, and the SE is the best among the three estimators.

KW - LINEX loss and risk function

KW - Linear regression

KW - Normal error

KW - Pre-test estimator

KW - Shrinkage estimator

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JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

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ER -

Shrinkage estimator of regression model under asymmetric loss

Abstract

Keywords

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