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Modified Ridge Regression Estimators
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University. (Nationalekonomi och Statistik)ORCID iD: 0000-0002-3416-5896
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]
Multicollinearty, Ridge regression, Monte Carlo simulation
National Category
Economics and Business
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-16199DOI: 10.1080/03610926.2011.593285ISI: 000321689700003OAI: oai:DiVA.org:lnu-16199DiVA: diva2:466883
Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2016-12-14Bibliographically approved

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Shukur, Ghazi
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CiteExportLink to record
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