Restricted ridge estimation
In 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).
Volume (Year): 65 (2003)
Issue (Month): 1 (October)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:65:y:2003:i:1:p:57-64. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.