Electronic Journal of Statistics

$\Phi$ admissibility of stochastic regression coefficients in a general multivariate random effects model under a generalized balanced loss function

Ming-Xiang Cao

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Abstract

The definitions of $\Phi$ optimality and $\Phi$ admissibility of stochastic regression coefficients are given in a general multivariate random effects model under the generalized balanced loss function. $\Phi$ admissibility of linear estimators of stochastic regression coefficients is investigated. Sufficient and necessary conditions for linear estimators to be $\Phi$ admissible in classes of homogeneous and nonhomogeneous linear estimators are obtained, respectively.

Article information

Source
Electron. J. Statist., Volume 6 (2012), 2332-2346.

Dates
First available in Project Euclid: 30 November 2012

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1354284422

Digital Object Identifier
doi:10.1214/12-EJS747

Mathematical Reviews number (MathSciNet)
MR3020265

Zentralblatt MATH identifier
1295.62008

Subjects
Primary: 62C15: Admissibility
Secondary: 62J12: Generalized linear models

Keywords
Balanced loss function linear estimators stochastic regression coefficients $\Phi$ optimality $\Phi$ admissibility

Citation

Cao, Ming-Xiang. $\Phi$ admissibility of stochastic regression coefficients in a general multivariate random effects model under a generalized balanced loss function. Electron. J. Statist. 6 (2012), 2332--2346. doi:10.1214/12-EJS747. https://projecteuclid.org/euclid.ejs/1354284422


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