A New Stochastic Restricted Liu Estimator in Weighted Mixed Regression

Author

Zuo, Weibing

Author_Institution

Coll. of Math. & Inf. Sci., North China Univ. of Water Conservancy & Hydroelectric Power, Zhengzhou, China

Volume

1

fYear

2009

fDate

12-14 Dec. 2009

Firstpage

245

Lastpage

248

Abstract

In this article, we consider the estimation for the vector of parameters in a linear regression model by unifying the sample and the prior information. A new Liu-type biased estimator called weighted stochastic restricted Liu estimator is proposed. Furthermore, necessary and sufficient conditions for the superiority of the weighted stochastic restricted Liu estimator over the Liu estimator, the weighted mixed estimator proposed by Scharin and Toutenburg (1990) and the weighted mixed Liu estimator proposed by Hu Yang (2009) in the mean squared error matrix sense are derived. Finally, a numerical example and a Monte Carlo simulation study are given to illustrate some of the theoretical results.

Keywords

Monte Carlo methods; matrix algebra; mean square error methods; regression analysis; stochastic processes; Monte Carlo simulation; linear regression model; mean squared error matrix; stochastic restricted Liu estimator; weighted mixed regression; Computational intelligence; Covariance matrix; Educational institutions; Information science; Linear regression; Mathematics; Stochastic processes; Testing; Vectors; Water conservation; Liu estimator; mean squared error matrix; weighted mixed Liu estimator; weighted mixed estimator; weighted stochastic restricted Liu estimator;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on

Conference_Location

Changsha

Print_ISBN

978-0-7695-3865-5

Type

conf

DOI

10.1109/ISCID.2009.68

Filename

5370912