Change search
ReferencesLink to record
Permanent link

Direct link
Performance of a new ridge regression estimator
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
2010 (English)In: Journal of the Association of Arab Universities for Basic and Applied Sciences, ISSN 1815-3852, Vol. 9, no 1, 23-26 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2010. Vol. 9, no 1, 23-26 p.
Keyword [en]
Mean squared error, Monte carlo simulations, Multicollinearity, Ridge parameter, Ridge regression
National Category
URN: urn:nbn:se:kth:diva-150331DOI: 10.1016/j.jaubas.2010.12.006ScopusID: 2-s2.0-79955364176OAI: diva2:742545

QC 20140902

Available from: 2014-09-02 Created: 2014-09-01 Last updated: 2014-09-02Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Al-Hassan, Yazid M.
By organisation
Mathematics (Dept.)

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 28 hits
ReferencesLink to record
Permanent link

Direct link