Bayes线性无偏最小方差估计相对于岭估计的优良性

The superiority of Bayes linear unbiased minimum variance estimator with respect to ridge estimator

在均方误差矩阵准则下研究了未知参数的Bayes线性无偏最小方差(BLUMV)估计相对于岭估计的优良性,在平衡损失风险函数准则下研究了未知参数的BLUMV估计相对于岭估计的优良性,并导出了在一定条件下BLUMV估计与最小二乘估计趋于一致.

The superiority of Bayes linear unbiased minimum variance （BLUMV） estimator with respect to ridge estimator of unknown parameter was studied in terms of the mean square error matrix criterion.Under balanced loss risk function criterion,The superiority of BLUMV estimator over ridge estimator of unknown parameter was investigated,and BLUMV estimator and least square estimator can converge to the same one under a certain condition.