约束条件下的线性贝叶斯估计  

Linear Bayesian Estimation under Constraint Conditions

作　　者：林盼盼 张凤月 王立春[1] LIN Pan-pan;ZHANG Feng-yue;WANG Li-chun(School of Science,Beijing Jiaotong University,Beijing 100044)

机构地区：[1]北京交通大学理学院,北京100044

出　　处：《工程数学学报》2020年第3期269-280,共12页Chinese Journal of Engineering Mathematics

基　　金：国家自然科学基金(11371051).

摘　　要：本文提出等式约束下线性模型中回归参数的线性贝叶斯估计,证明其在均方误差矩阵准则下相对于约束最小二乘估计的优越性,并采用蒙特卡洛模拟和数值算例验证其优越性.In this paper,a linear Bayesian estimator is derived for the regression parameters in a linear model with equality constraints.The superiority of the linear Bayesian estimator over the constrained least square estimator is proved in terms of the mean square error matrix criterion.Monte Carlo simulations and a numerical example are employed to investigate the superiorities of the proposed linear Bayesian estimator.

关 键 词：等式约束 线性贝叶斯估计 约束最小二乘估计 均方误差矩阵 蒙特卡洛模拟 

分 类 号：O212.8[理学—概率论与数理统计]