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Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorBárzana, Marta García-
dc.contributor.authorColubi, Ana-
dc.contributor.authorKontoghiorghes, Erricos John-
dc.contributor.otherΚοντογιώργης, Ερρίκος-
dc.date.accessioned2019-07-29T08:45:12Z-
dc.date.available2019-07-29T08:45:12Z-
dc.date.issued2015-01-01-
dc.identifier.citationAdvances in Intelligent Systems and Computing Volume 315, 2015, Pages 185-191-
dc.identifier.issn21945357-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/14733-
dc.description.abstract© Springer International Publishing Switzerland 2015. A multiple interval-valued linear regression model considering all the cross-relationships between the mids and spreads of the intervals has been introduced recently. A least-squares estimation of the regression parameters has been carried out by transforming a quadratic optimization problem with inequality constraints into a linear complementary problem and using Lemke’s algorithm to solve it. Due to the irrelevance of certain cross-relationships, an alternative estimation process, the LASSO (Least Absolut Shrinkage and Selection Operator), is developed. A comparative study showing the differences between the proposed estimators is provided.-
dc.language.isoen-
dc.relation.ispartofAdvances in Intelligent Systems and Computing-
dc.rights© Springer International Publishing 2015.-
dc.subjectInterval-valued data-
dc.subjectLasso estimation-
dc.subjectMultiple regression-
dc.subjectConstraint theory-
dc.titleLasso estimation of an interval-valued multiple regression model-
dc.typeArticle-
dc.collaborationUniversity of Oviedo-
dc.collaborationCyprus University of Technology-
dc.subject.categoryEconomics and Business-
dc.journalsSubscription Journal-
dc.countrySpain-
dc.countryCyprus-
dc.subject.fieldSocial Sciences-
dc.publicationPeer Reviewed-
dc.identifier.doi10.1007/978-3-319-10765-3_22-
dc.identifier.scopus2-s2.0-84921461829-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84921461829-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.relation.volume315-
cut.common.academicyear2015-2016-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
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