广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (05): 5-8.doi: 10.3969/j.issn.1007-7162.2016.05.002

• 综合研究 • 上一篇    下一篇

Bayes线性无偏估计关于误差协方差及先验分布的稳健性

邱红兵   

  1. 广东工业大学 应用数学学院, 广东 广州 510520
  • 收稿日期:2015-12-01 出版日期:2016-09-10 发布日期:2016-09-10
  • 作者简介:邱红兵(1974-),男,副教授,主要研究方向为线性模型.
  • 基金资助:

    国家自然科学基金资助项目(11401114);国家社会科学基金资助项目(11CTJ008)

Robustness of Bayes Linear Unbiased Estimator in Terms of Error Covariance and Prior Distributions

Qiu Hong-bing   

  1. School of Applied Mathematics, Guangdong University of Technology, Guangzhou 510520,China
  • Received:2015-12-01 Online:2016-09-10 Published:2016-09-10

摘要:

对于线性模型中未知参数估计的稳健性的研究,一直是统计学中的一个热点.本文研究线性模型中回归系数的Bayes线性无偏估计关于误差协方差及先验分布的稳健性问题,分别得到当误差协方差改变、先验分布改变或误差协方差和先验分布同时改变时,Bayes线性无偏估计还保持其最优性的充分必要条件.

关键词: 线性模型;Bayes线性无偏估计;稳健性;先验分布

Abstract:

The research that focuses on the robustness for the estimation of unknown parameters in the linear model has been a hot topic of statistics. In this paper, the robustness of Bayes linear unbiased estimator of the regression coefficients in the linear model in terms of error covariance and prior distributions are discussed, and the necessary and sufficient conditions for Bayes linear unbiased estimator holding its optimality when error covariance varies, or prior distributions vary, or error covariance and prior distributions vary, are respectively obtained.

Key words: linear model; Bayes linear unbiased estimator; robustness; prior distribution

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