A comparison of three prediction based methods of choosing the ridge regression parameter k

dc.contributor.authorGatz, Philip L., Jr.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T21:49:45Zen
dc.date.adate2013-11-15en
dc.date.available2014-03-14T21:49:45Zen
dc.date.issued1985-07-02en
dc.date.rdate2013-11-15en
dc.date.sdate2013-11-15en
dc.description.abstractA solution to the regression model y = xβ+ε is usually obtained using ordinary least squares. However, when the condition of multicollinearity exists among the regressor variables, then many qualities of this solution deteriorate. The qualities include the variances, the length, the stability, and the prediction capabilities of the solution. An analysis called ridge regression introduced a solution to combat this deterioration (Hoerl and Kennard, 1970a). The method uses a solution biased by a parameter k. Many methods have been developed to determine an optimal value of k. This study chose to investigate three little used methods of determining k: the PRESS statistic, Mallows' C<sub>k</sub>. statistic, and DF-trace. The study compared the prediction capabilities of the three methods using data that contained various levels of both collinearity and leverage. This was completed by using a Monte Carlo experiment.en
dc.description.degreeMaster of Scienceen
dc.format.extentvii, 64 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-11152013-040304en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11152013-040304/en
dc.identifier.urihttp://hdl.handle.net/10919/45724en
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V855_1985.G479.pdfen
dc.relation.isformatofOCLC# 13052481en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1985.G479en
dc.subject.lcshMulticollinearityen
dc.subject.lcshPrediction theoryen
dc.subject.lcshRidge regression (Statistics)en
dc.titleA comparison of three prediction based methods of choosing the ridge regression parameter ken
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen
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