中文摘要：

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（Bayes linear unbiased minimum variance estimator, BLUMV）估计相对于最小二乘（1eastsquare，LS）估计的优良性，并讨论了3种不同相对效率的界．在predictive Pitman closeness（PRPC）准则下研究了BLUMV估计相对于LS估计的优良性．

英文摘要：

The superiority of Bayes linear unbiased minimum variance （BLUMV） estimator with respect to least square （LS） estimator of unknown parameters was studied in terms of the mean square error matrix criterion, and the bounds of three relative efficiencies were obtained respectively. The superiority of the BLUMV estimator over LS estimator was studied in terms of the predictive Pitman closeness （PRPC） criterion.