Article ID Journal Published Year Pages File Type
7696034 Journal of the Association of Arab Universities for Basic and Applied Sciences 2016 7 Pages PDF
Abstract
This paper proposes an adjusted ridge regression estimator for β for the linear regression model. The merit of the proposed estimator is that it does not require estimating the ridge parameter k unlike other existing estimators. We compared our estimator with an ordinary least squares (LS) estimator and with some well known estimators proposed by Hoerl and Kennard (1970), ordinary ridge regression (RR) estimator and generalized ridge regression (GR) and some estimators proposed by Kibria (2003) among others. A simulation study has been conducted and compared for the performance of the estimators in the sense of smaller mean square error (MSE). It appears that the proposed estimator is promising and can be recommended to the practitioners.
Related Topics
Physical Sciences and Engineering Chemistry Chemistry (General)
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