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Risk Comparison of Improved Estimators in a Linear Regression Model with Multivariate t Errors under Balanced Loss Function
Joint Authors
Li, Qingguo
Hu, Guikai
Yu, Shenghua
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-06
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Under a balanced loss function, we derive the explicit formulae of the risk of the Stein-rule (SR) estimator, the positive-part Stein-rule (PSR) estimator, the feasible minimum mean squared error (FMMSE) estimator, and the adjusted feasible minimum mean squared error (AFMMSE) estimator in a linear regression model with multivariate t errors.
The results show that the PSR estimator dominates the SR estimator under the balanced loss and multivariate t errors.
Also, our numerical results show that these estimators dominate the ordinary least squares (OLS) estimator when the weight of precision of estimation is larger than about half, and vice versa.
Furthermore, the AFMMSE estimator dominates the PSR estimator in certain occasions.
American Psychological Association (APA)
Hu, Guikai& Li, Qingguo& Yu, Shenghua. 2014. Risk Comparison of Improved Estimators in a Linear Regression Model with Multivariate t Errors under Balanced Loss Function. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-447965
Modern Language Association (MLA)
Hu, Guikai…[et al.]. Risk Comparison of Improved Estimators in a Linear Regression Model with Multivariate t Errors under Balanced Loss Function. Journal of Applied Mathematics No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-447965
American Medical Association (AMA)
Hu, Guikai& Li, Qingguo& Yu, Shenghua. Risk Comparison of Improved Estimators in a Linear Regression Model with Multivariate t Errors under Balanced Loss Function. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-447965
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-447965