Efficiency of the generalized difference-based Liu estimators in semiparametric regression models with correlated errors


Akdeniz F., Duran E. A. , Roozbeh M., Arashi M.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.85, no.1, pp.147-165, 2015 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 85 Issue: 1
  • Publication Date: 2015
  • Doi Number: 10.1080/00949655.2013.806924
  • Title of Journal : JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Page Numbers: pp.147-165

Abstract

In this paper, a generalized difference-based estimator is introduced for the vector parameter β in the semiparametric regression model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter β in the semiparametric regression model. Under the linear nonstochastic constraint Rβ=r, the generalized restricted difference-based Liu estimator is given. The risk function for the βˆGRD(η) associated with weighted balanced loss function is presented. The performance of the proposed estimators is evaluated by a simulated data set.

In this paper, a generalized difference-based estimator is introduced for the vector parameter beta in the semiparametric regression model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter beta in the semiparametric regression model. Under the linear nonstochastic constraint R beta=r, the generalized restricted difference-based Liu estimator is given. The risk function for the beta(GRD)(eta) associated with weighted balanced loss function is presented. The performance of the proposed estimators is evaluated by a simulated data set.