摘要
考察一般Gauss-Markov模型中未知参数向量β的估计的改造问题,进一步讨论了方兴等人提出的一种估计的相对效率,对其部分结果进行推广,得到LSE相对于一般广义岭估计的效率的下界.
The problem of the best linear unbiased estimate in the general Gauss-Markov model is considered. The relative efficiency of the estimate proposed by Fangxing is generalized and the lower bound of efficiencies of linear unbiased estimate with respect to the general ridge estimate is obtained.
出处
《三明学院学报》
2007年第2期127-128,133,共3页
Journal of Sanming University
关键词
最小二乘估计(LSE)
广义岭估计
效率
下界
least squares estimate
generalized ridge estimate
relative efficiency
lower bound.
