New versions of Liu-Type estimator in weighted and non-weighted mixed regression model
Other Title(s)
إصدارات جديدة لمقدر ليو-تايب في نموذج الانحدار المختلط المرجح و غير المرجح
Author
Source
Issue
Vol. 17, Issue 1 (sup) (31 Mar. 2020), pp.361-370, 10 p.
Publisher
University of Baghdad College of Science for Women
Publication Date
2020-03-31
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
al-Hiti, Mustafa Ismail Nayif. 2020. New versions of Liu-Type estimator in weighted and non-weighted mixed regression model. Baghdad Science Journal،Vol. 17, no. 1 (sup), pp.361-370.
https://search.emarefa.net/detail/BIM-970043
Modern Language Association (MLA)
al-Hiti, Mustafa Ismail Nayif. New versions of Liu-Type estimator in weighted and non-weighted mixed regression model. Baghdad Science Journal Vol. 17, no. 1 (Supplement) (Mar. 2020), pp.361-370.
https://search.emarefa.net/detail/BIM-970043
American Medical Association (AMA)
al-Hiti, Mustafa Ismail Nayif. New versions of Liu-Type estimator in weighted and non-weighted mixed regression model. Baghdad Science Journal. 2020. Vol. 17, no. 1 (sup), pp.361-370.
https://search.emarefa.net/detail/BIM-970043
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 369
Record ID
BIM-970043