平衡损失函数下Bayes线性无偏最小方差估计的优良性

J4 ›› 2011, Vol. 46 ›› Issue (11): 89-95.

平衡损失函数下Bayes线性无偏最小方差估计的优良性

刘谢进¹, 缪柏其²

1. 淮南师范学院数学与计算科学系, 安徽淮南 232038; 2. 中国科学技术大学统计与金融系, 安徽合肥 230026

收稿日期:2010-12-10 出版日期:2011-11-20 发布日期:2011-11-30
作者简介:刘谢进(1971- ),男,硕士,副教授,研究方向为数理统计. Email:hnsylxj@163.com
基金资助:
国家自然科学基金资助项目(10471135); 淮南师范学院科研基金资助项目(2010LK07)

The superiority of the Bayes linear unbiased minimum Variance estimator under balanced loss function

LIU Xie-jin¹, MIAO Bai-qi²

1. Department of Mathematics and Computional Science, Huainan Normal University, Huainan 232038, Anhui, China;
2. Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, Anhui, China

Received:2010-12-10 Online:2011-11-20 Published:2011-11-30

摘要/Abstract

摘要：

在平衡损失风险函数准则下研究了未知参数的Bayes线性无偏最小方差(BLUMV)估计相对于最优加权最小二乘(OWLS)估计的优良性,并导出在一定条件下二者趋于一致。在PRPC(predictive Pitman closeness criterion)准则下研究了BLUMV估计相对于OWLS估计的优良性。

关键词: Bayes线性无偏最小方差估计;最小二乘估计;最优加权最小二乘估计;平衡损失风险函数准则;PRPC准则

Abstract:

The superiority of the Bayes linear unbiased minimum variance (BLUMV) estimator with respect to the optimally weighted least square (OWLS) estimator of unknown parameter was studied in terms of the balanced loss risk function criterion, and the two estimators can converge to the same one under a certain condition. The superiority of the BLUMV estimator over the OWLS estimator was studied under predictive Pitman closeness (PRPC) criterion.

Key words: Bayes linear unbiased minimum variance estimator; least square estimator; optimally weighted least square estimator; balanced loss risk function criterion; predictive Pitman closeness criterion

刘谢进1, 缪柏其2. 平衡损失函数下Bayes线性无偏最小方差估计的优良性[J]. J4, 2011, 46(11): 89-95.

LIU Xie-jin1, MIAO Bai-qi2. The superiority of the Bayes linear unbiased minimum Variance estimator under balanced loss function[J]. J4, 2011, 46(11): 89-95.

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