Improved estimation in regression with varying penalty

Zahirul Hoque; Shahadut Hossain

doi:10.1080/15598608.2012.673878

Improved estimation in regression with varying penalty

Zahirul Hoque, Shahadut Hossain

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

5 Citations (Scopus)

Abstract

This article considers the estimation of the intercept parameter of a simple linear regression model under asymmetric linex loss. The least-squares estimator (LSE) and the preliminary test estimator (PTE) are defined. The risk functions of the estimators are derived. The moment-generating function (MGF) and the first two moments of the PTE are shown. The risk of the PTE is compared with that of the LSE. The analyses show that if the nonsample prior information about the value of the parameter is not too far from its true value, the PTE dominates the traditional LSE.

Original language	English
Pages (from-to)	260-273
Number of pages	14
Journal	Journal of Statistical Theory and Practice
Volume	6
Issue number	2
DOIs	https://doi.org/10.1080/15598608.2012.673878
Publication status	Published - Jun 1 2012

Keywords

Asymmetric loss
Intercept parameter
Preliminary test estimator
Prior information

ASJC Scopus subject areas

Statistics and Probability

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10.1080/15598608.2012.673878

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abstract = "This article considers the estimation of the intercept parameter of a simple linear regression model under asymmetric linex loss. The least-squares estimator (LSE) and the preliminary test estimator (PTE) are defined. The risk functions of the estimators are derived. The moment-generating function (MGF) and the first two moments of the PTE are shown. The risk of the PTE is compared with that of the LSE. The analyses show that if the nonsample prior information about the value of the parameter is not too far from its true value, the PTE dominates the traditional LSE.",

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N2 - This article considers the estimation of the intercept parameter of a simple linear regression model under asymmetric linex loss. The least-squares estimator (LSE) and the preliminary test estimator (PTE) are defined. The risk functions of the estimators are derived. The moment-generating function (MGF) and the first two moments of the PTE are shown. The risk of the PTE is compared with that of the LSE. The analyses show that if the nonsample prior information about the value of the parameter is not too far from its true value, the PTE dominates the traditional LSE.

AB - This article considers the estimation of the intercept parameter of a simple linear regression model under asymmetric linex loss. The least-squares estimator (LSE) and the preliminary test estimator (PTE) are defined. The risk functions of the estimators are derived. The moment-generating function (MGF) and the first two moments of the PTE are shown. The risk of the PTE is compared with that of the LSE. The analyses show that if the nonsample prior information about the value of the parameter is not too far from its true value, the PTE dominates the traditional LSE.

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Improved estimation in regression with varying penalty

Abstract

Keywords

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