University of Bahrain
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Performance of a New Ridge Regression Estimator

Show simple item record Al-Hassan, Yazid M. 2018-07-25T10:52:14Z 2018-07-25T10:52:14Z 2010
dc.identifier.issn 1815-3852
dc.description.abstract Ridge regression estimator has been introduced as an alternative to the ordinary least squares estimator (OLS) in the presence of multicollinearity. Several studies concerning ridge regression have dealt with the choice of the ridge parameter. Many algorithms for the ridge parameter have been proposed in the statistical literature. In this article, a new method for estimating ridge parameter is proposed. A simulation study has been made to evaluate the performance of the proposed estimator based on the mean squared error (MSE) criterion. The evaluation has been done by comparing the MSEs of the proposed estimator with other well-known estimators. In the presence of multicollinearity, the simulation study indicates that under certain conditions the proposed estimator performs better than other estimators. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Mean squared error
dc.subject Monte Carlo simulations
dc.subject Multicollinearity
dc.subject Ridge parameter
dc.subject Ridge regression
dc.title Performance of a New Ridge Regression Estimator en_US
dc.type Article en_US
dc.source.title Arab Journal of Basic and Applied Sciences
dc.abbreviatedsourcetitle AJBAS

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