A NEW STOCHASTIC RESTRICTED BIASED ESTIMATOR UNDER HETEROSCEDASTIC OR CORRELATED ERROR

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DC Field	Value	Language
dc.contributor.author	Mustafa Ismaeel Alheety	-
dc.date.accessioned	2022-10-26T18:29:33Z	-
dc.date.available	2022-10-26T18:29:33Z	-
dc.date.issued	2009	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/7000	-
dc.description.abstract	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.	en_US
dc.language.iso	en	en_US
dc.publisher	Probability and Statistics	en_US
dc.subject	Heteroscedasticity, generalized least squares estimator,	en_US
dc.subject	stochastic restricted Liu estimator.	en_US
dc.title	A NEW STOCHASTIC RESTRICTED BIASED ESTIMATOR UNDER HETEROSCEDASTIC OR CORRELATED ERROR	en_US
dc.type	Article	en_US
Appears in Collections:	قسم الرياضيات

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