Volume 15, 2011
|Page(s)||30 - 40|
|Published online||03 February 2011|
A new stochastic restricted biased estimator under heteroscedastic or correlated error
Department of Mathematics, Al-Anbar University, Ramadi, Iraq; firstname.lastname@example.org
Revised: 9 January 2009
In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GORR, GLS and the stochastic restricted Liu estimator (SRLE) [Yang and Xu, Statist. Papers 50 (2007) 639–647] are examined in terms of matrix mean square error criterion. A numerical example is considered to illustrate the theoretical results.
Mathematics Subject Classification: 62J05 / 62J07
Key words: Heteroscedasticity / generalized least squares estimator / stochastic restricted Liu estimator
© EDP Sciences, SMAI, 2011
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