New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model

Authors

Mustafa Ismaeel Naif Alheety, Department of Mathematics, College of Education for Pure Sciences, University of Anbar, Anbar, IraqFollow

Abstract

This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

Keywords

Liu estimator, Mean squared error matrix, Mixed estimator, Stochastic restricted Liu estimator, Weighted mixed Liu estimator. Mathematics Subject Classification Primary: 62J05; Secondary 62J07.

Article Type

Supplemental Issue

How to Cite this Article

Alheety, Mustafa Ismaeel Naif (2020) "New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model," Baghdad Science Journal: Vol. 17: Iss. 1, Article 50.
DOI: https://doi.org/10.21123/bsj.2020.17.1(Suppl.).0361