Restricted ridge estimation
AbstractIn this paper, we introduce a ridge estimator for the vector of parameters in a linear regression model when additional linear restrictions on the parameter vector are assumed to hold. The estimator is a generalization of the well-known restricted least-squares estimator and is confined to the (affine) subspace which is generated by the restrictions. Necessary and sufficient conditions for the superiority of the new estimator over the restricted least-squares estimator are derived. Our new estimator is not to be confounded with the restricted ridge regression estimator introduced by Sarkar (Comm. Statist. Theory Methods 21 (1992) 1987).
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 65 (2003)
Issue (Month): 1 (October)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- M. Alkhamisi, 2010. "Simulation study of new estimators combining the SUR ridge regression and the restricted least squares methodologies," Statistical Papers, Springer, vol. 51(3), pages 651-672, September.
- Hu Yang & Jianwen Xu, 2011. "Preliminary test Liu estimators based on the conflicting W, LR and LM tests in a regression model with multivariate Student-t error," Metrika, Springer, vol. 73(3), pages 275-292, May.
- Yalian Li & Hu Yang, 2010. "A new stochastic mixed ridge estimator in linear regression model," Statistical Papers, Springer, vol. 51(2), pages 315-323, June.
- Özkale, M. Revan, 2009. "A stochastic restricted ridge regression estimator," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1706-1716, September.
- Jahufer, Aboobacker & Jianbao, Chen, 2009. "Assessing global influential observations in modified ridge regression," Statistics & Probability Letters, Elsevier, vol. 79(4), pages 513-518, February.
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