BIASED ESTIMATOR BASED ON DIAGNOSIS AND MEASURE OF MULTICOLLINEARITY
基于复共线性诊断和度量的有偏估计

On the basis of diagnosis and measure of multicollinearity,a new biased estimator of unknown parameters called partial ridge(PR)estimator is proposed for Gauss-Markov model.Its properties are discussed,and some important conclusions are drawn.The determination of biased parameter in the PR estimator is discussed too.Both theoretical and computational results demonstrate that the PR estimator is a effective biased estimator for overcoming the effect of multicollinearity and is superior to the ordinary ridge estimator.