吉林大学学报(理学版)

• 数学 • 上一篇    下一篇

正态-逆Gamma先验下线性模型中回归系数和误差方差Bayes估计的改进

许凯, 何道江   

  1. 安徽师范大学 数学计算机科学学院, 安徽 芜湖 241003
  • 收稿日期:2013-06-04 出版日期:2014-03-26 发布日期:2014-03-20
  • 通讯作者: 何道江 E-mail:djheahnu163.com

Improvement of Bayes Estimation of Regression Coeffcientsand Error Variance in Linear Model with Respect toNormalInverse Gamma Priors

XU Kai, HE Daojiang   

  1. School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241003, Anhui Province, China
  • Received:2013-06-04 Online:2014-03-26 Published:2014-03-20
  • Contact: HE Daojiang E-mail:djheahnu163.com

摘要:

在正态逆Gamma先验下, 研究线性模型中回归系数和误差方差Bayes估计的优良性, 改进了已有的结果, 去掉了附加条件. 在Pitman准则下, 证明回归系数的Bayes估计优于最小二乘估计(LSE), 并讨论误差方差的Bayes估计在均方误差准则下相对于LSE的优良性. 最后进行Monte Carlo模拟研究, 进一步验证了理论结果.

关键词: Bayes估计, Bayes Pitman准则, 均方误差准则, 最小二乘估计

Abstract:

The superiority of Bayes estimation of regression coeffcients and error variance in linear model was studied based on normalinverse Gamma priors. The existed results were complemented without the additive conditions. It was shown that the Bayes estimation of regression coefficients is superior to the least squares estimator (LSE) under the Pitman closeness criterion. And the superiority of the Bayes estimation of error variance over LSE was also investigated in terms of the mean square error criterion. Finally, a Monte Carlo simulation was carried out to verify the theoretical results.

Key words: Bayes estimation, least squares estimation, Bayes Pitman , criterion, mean square error criterion

中图分类号: 

  • O212.2