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Estimation of a normal mean relative to balanced loss functions
Authors:N. Sanjari Farsipour  A. Asgharzadeh
Affiliation:(1) Department of Statics, Shiraz University, 71454 Shiraz, Iran
Abstract:LetX 1,…,X nbe a random sample from a normal distribution with mean θ and variance σ2. The problem is to estimate θ with Zellner's (1994) balanced loss function, 
$$L_B left( {hat theta ,theta } right) = frac{omega }{n}sum {_1^n left( {X_i  - hat theta } right)^2 }  + left( {1 - w} right)left( {theta ,hat theta } right)^2 $$
% MathType!End!2!1!, where 0<ω<1. It is shown that the sample mean 
$$bar X$$
% MathType!End!2!1!, is admissible. More generally, we investigate the admissibility of estimators of the form 
$$alpha bar X + b$$
% MathType!End!2!1! under 
$$L_B left( {hat theta ,theta } right)$$
% MathType!End!2!1!. We also consider the weighted balanced loss function, 
$$L_W left( {hat theta ,theta } right) = omega qleft( theta  right)frac{{sum {_1^n left( {X_i  - hat theta } right)^2 } }}{n} + left( {1 - w} right)qleft( theta  right)left( {theta ,hat theta } right)^2 $$
% MathType!End!2!1!, whereq(θ) is any positive function of θ, and the class of admissible linear estimators is obtained under such loss withq(θ) =e θ .
Keywords:Admissibility  Balanced loss function  Bayes estimtor  Inadmissibility  Weighted balanced loss function
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