约束条件下的线性贝叶斯估计

Linear Bayesian Estimation under Constraint Conditions

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.