Efficiency of a Liu-type estimator in semiparametric regression models


Duran E. A. , Akdeniz F., Hu H.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, vol.235, no.5, pp.1418-1428, 2011 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 235 Issue: 5
  • Publication Date: 2011
  • Doi Number: 10.1016/j.cam.2010.08.028
  • Title of Journal : JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
  • Page Numbers: pp.1418-1428

Abstract

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.