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Modified Ridge Regression Estimators
Department of Mathematics, King Khalid University, Abha, Saudi Arabia.
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistics)
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistics)
2013 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 42, no 8, 1476-1487 p.Article in journal (Refereed) Published
Abstract [en]

Ridge regression is a variant of ordinary multiple linear regression whose goal is to circumvent the problem of predictors collinearity. It gives up the Ordinary Least Squares (OLS) estimator as a method for estimating the parameters [] of the multiple linear regression model [] . Different methods of specifying the ridge parameter k were proposed and evaluated in terms of Mean Square Error (MSE) by simulation techniques. Comparison is made with other ridge-type estimators evaluated elsewhere. The new estimators of the ridge parameters are shown to have very good MSE properties compared with the other estimators of the ridge parameter and the OLS estimator. Based on our results from the simulation study, we may recommend the new ridge parameters to practitioners.

Place, publisher, year, edition, pages
2013. Vol. 42, no 8, 1476-1487 p.
Keyword [en]
Monte Carlo simulation, Multicollinearty, Ridge regression
National Category
Economics Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-17322DOI: 10.1080/03610926.2011.593285Local ID: IHHEFSISOAI: oai:DiVA.org:hj-17322DiVA: diva2:480744
Available from: 2012-01-19 Created: 2012-01-19 Last updated: 2014-03-06Bibliographically approved

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