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dc.contributor.authorMuniz, Gisela
dc.contributor.authorGolam Kibria, B. M.
dc.contributor.authorMansson, Kristofer Mansson
dc.contributor.authorShukur, Ghazi
dc.date.accessioned2013-05-16T16:41:13Z
dc.date.available2013-05-16T16:41:13Z
dc.date.issued2012
dc.identifier.citationMuniz, Gisela [et al.]. On developing ridge regression parameters: a graphical investigation. "SORT", vol. 36, núm. 2, p. 115-138.
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2099/13316
dc.description.abstractIn this paper we review some existing and propose some new est imators for estimating the ridge parameter. All in all 19 different estimators have been stud ied. The investigation has been carried out using Monte Carlo simulations. A large number of differe nt models have been investigated where the variance of the random error, the number of variabl es included in the model, the correlations among the explanatory variables, the sample s ize and the unknown coefficient vector were varied. For each model we have performed 2000 replicati ons and presented the results both in term of figures and tables. Based on the simulation study, w e found that increasing the number of correlated variable, the variance of the random error and increasing the correlation between the independent variables have negative effect on the mean s quared error. When the sample size increases the mean squared error decreases even when the cor relation between the independent variables and the variance of the random error are large. In a ll situations, the proposed estimators have smaller mean squared error than the ordinary least squa res and other existing estimators
dc.format.extent24 p.
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2012, vol. 36, núm. 2
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.lcshMathematical statistics
dc.subject.otherLinear model
dc.subject.otherLSE
dc.subject.otherMSE
dc.subject.otherMonte Carlo simulations
dc.subject.othermulticoll inearity
dc.subject.otherridge regression
dc.titleOn developing ridge regression parameters: a graphical investigation
dc.typeArticle
dc.subject.lemacEstadística matemàtica
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62F Parametric inference
dc.subject.amsClassificació AMS::62 Statistics::62J Linear inference, regression
dc.rights.accessOpen Access
upcommons.citation.authorMuniz, Gisela; Golam Kibria, B. M.; Mansson, Kristofer Mansson; Shukur, Ghazi
upcommons.citation.publishedtrue
upcommons.citation.publicationNameSORT
upcommons.citation.volume36
upcommons.citation.number2
upcommons.citation.startingPage115
upcommons.citation.endingPage138


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