摘要
针对一般带约束的最小二乘估计(ORLSE)在参数估计中处理复共线性的不足,引入随机线性约束,提出了约束k-d估计方法。在均方误差(MSE)下,讨论了它的性质,得到了四个主要结果,与带约束的最小二乘估计ORLSE、约束岭估计(RRE)和约束型Liu估计比较,得出更好的结论。
In order to overcome the shortage of the multicollinearity in ordinary restricted least square estimation with parameter estimate,based on the stochastic linear restrictions,a new estimation as restricted linear k-d-type estimation is proposed.In the mean squared error sense,discuss its properties,get three main results,compare with the ordinary restricted least squares estimation,and the restricted ridge estimation,the method we proposed was superior.
出处
《数学理论与应用》
2010年第4期103-106,共4页
Mathematical Theory and Applications
关键词
线性回归
复共线性
k-d型估计
均方误差
Linear regression Multicollinearity k-d estinmate Mean square error sense
