Shrinkage estimator in normal mean vector estimation based on conditional maximum likelihood estimators

被引:3
|
作者
Park, Junyong [1 ]
机构
[1] Univ Maryland Baltimore Cty, Dept Math & Stat, Baltimore, MD 21250 USA
关键词
Shrinkage; Sparsity; Empirical Bayes; Conditional maximum likelihood estimate; Mean vector; Stein's risk unbiased estimate; WAVELET SHRINKAGE;
D O I
10.1016/j.spl.2014.06.005
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Estimation of normal mean vector has broad applications such as small area estimation, estimation of nonparametric functions and estimation of wavelet coefficients. In this paper, we propose a new shrinkage estimator based on conditional maximum likelihood estimator incorporating with Stein's risk unbiased estimator (SURE) when data have the normality. We present some theoretical work and provide numerical studies to compare with some existing methods. (C) 2014 Elsevier B.V. All rights reserved.
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页码:1 / 6
页数:6
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