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, cilt.85, ss.147-165, 2015 (SCI İndekslerine Giren Dergi)

  • Cilt numarası: 85 Konu: 1
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1080/00949655.2013.806924
  • Dergi Adı: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Sayfa Sayısı: ss.147-165

Özet

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.

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.