Efficiency of a Liu-type estimator in semiparametric regression models

In this paper we consider the semiparametric regression model, y = X beta + f + epsilon. Recently, Hu [11] proposed ridge regression estimator in a semiparametric regression model. We introduce a Liu-type (combined ridge-Stein) estimator (LTE) in a semiparametric regression model. Firstly, Liu-type estimators of both beta and f are attained without a restrained design matrix. Secondly, the LTE estimator of beta is compared with the two-step estimator in terms of the mean square error. We describe the almost unbiased Liu-type estimator in semiparametric regression models. The almost unbiased Liu-type estimator is compared with the Liu-type estimator in terms of the mean squared error matrix. A numerical example is provided to show the performance of the estimators. (C) 2010 Elsevier B.V. All rights reserved.