A new stochastic restricted Liu-type estimator in linear regression model

Abstract

In this paper, we proposed an alternative stochastic restricted Liu-type estimator for the vector of parameters in a linear regression model. The new estimator is a combination of ordinary mixed estimator and Liu-Type estimator , which was proposed by Liu. Necessary and sufficient conditions for the superiority of new stochastic restricted Liu-type estimator over the ordinary mixed estimator and the Liu-type estimator in the mean squared error matrix sense are derived for the two cases in which the parametric restrictions are correct and are not correct. In particular, we showed that was superior in the mean squared error matrix sense over both and to the Liu-type estimator introduced by Liu (2003).