Superiority of the Stochastic Restricted Liu Estimator under misspecification

This paper deals with the use of correct prior infromation in the estimation of regression coefficients when the regression model is misspecified due to the exclusion of some relevant regressor variables. In particular, the attention is focused on the Stochastic Restricted Liu estimator introduced by Hubert and Wijekoon (2004), which outperforms Liu estimator with respect to the matrix mean squared error matrix criterion. Further the superiority of the Stochastic Restricted Liu predictor over the Liu predictor is also examined, and concluded that there are situations where the Stochastic Restricted Liu predictor outperforms the Liu predictor with respect to the mean squared error matrix criterion even the model is misspecified