Comparison of ridge and other shrinkage estimation techniques

 

Show simple item record

dc.contributor.advisor Thiart, Christien en_ZA
dc.contributor.author Vumbukani, Bokang C en_ZA
dc.date.accessioned 2014-07-30T17:43:34Z
dc.date.available 2014-07-30T17:43:34Z
dc.date.issued 2006 en_ZA
dc.identifier.citation Vumbukani, B. 2006. Comparison of ridge and other shrinkage estimation techniques. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/4364
dc.description Includes bibliographical references.
dc.description.abstract Shrinkage estimation is an increasingly popular class of biased parameter estimation techniques, vital when the columns of the matrix of independent variables X exhibit dependencies or near dependencies. These dependencies often lead to serious problems in least squares estimation: inflated variances and mean squared errors of estimates unstable coefficients, imprecision and improper estimation. Shrinkage methods allow for a little bias and at the same time introduce smaller mean squared error and variances for the biased estimators, compared to those of unbiased estimators. However, shrinkage methods are based on the shrinkage factor, of which estimation depends on the unknown values, often computed from the OLS solution. We argue that the instability of OLS estimates may have an adverse effect on performance of shrinkage estimators. Hence a new method for estimating the shrinkage factors is proposed and applied on ridge and generalized ridge regression. We propose that the new shrinkage factors should be based on the principal components instead of the unstable OLS estimates. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Statistical Sciences en_ZA
dc.title Comparison of ridge and other shrinkage estimation techniques en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Statistical Sciences en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Vumbukani, B. C. (2006). <i>Comparison of ridge and other shrinkage estimation techniques</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/4364 en_ZA
dc.identifier.chicagocitation Vumbukani, Bokang C. <i>"Comparison of ridge and other shrinkage estimation techniques."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2006. http://hdl.handle.net/11427/4364 en_ZA
dc.identifier.vancouvercitation Vumbukani BC. Comparison of ridge and other shrinkage estimation techniques. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2006 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/4364 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Vumbukani, Bokang C AB - Shrinkage estimation is an increasingly popular class of biased parameter estimation techniques, vital when the columns of the matrix of independent variables X exhibit dependencies or near dependencies. These dependencies often lead to serious problems in least squares estimation: inflated variances and mean squared errors of estimates unstable coefficients, imprecision and improper estimation. Shrinkage methods allow for a little bias and at the same time introduce smaller mean squared error and variances for the biased estimators, compared to those of unbiased estimators. However, shrinkage methods are based on the shrinkage factor, of which estimation depends on the unknown values, often computed from the OLS solution. We argue that the instability of OLS estimates may have an adverse effect on performance of shrinkage estimators. Hence a new method for estimating the shrinkage factors is proposed and applied on ridge and generalized ridge regression. We propose that the new shrinkage factors should be based on the principal components instead of the unstable OLS estimates. DA - 2006 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2006 T1 - Comparison of ridge and other shrinkage estimation techniques TI - Comparison of ridge and other shrinkage estimation techniques UR - http://hdl.handle.net/11427/4364 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record