Summary: Consider the linear regression model
in the usual notation. In the presence of multicollinearity certain biased estimators like the ordinary ridge regression estimator
and the Liu estimator
introduced by K. Liu
[Commun. Stat., Theory Methods 22, 393-402 (1993; Zbl 0784.62065
)], or improved ridge and Liu estimators are used to outperform the ordinary least squares estimates in the linear regression model. We compare the (almost unbiased) generalized ridge regression estimator with the (almost unbiased) generalized Liu estimator in the matrix mean square error sense.