Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14719
DC FieldValueLanguage
dc.contributor.authorColubi, Ana-
dc.contributor.authorGarciá-Bárzana, Marta-
dc.contributor.authorKontoghiorghes, Erricos John-
dc.contributor.authorRamos-Guajardo, Ana Belén-
dc.date.accessioned2019-07-25T11:59:02Z-
dc.date.available2019-07-25T11:59:02Z-
dc.date.issued2020-06-01-
dc.identifier.citationComputational Statistics, 2020, vol. 35, no. 2, pp. 755-773en_US
dc.identifier.issn09434062-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/14719-
dc.description.abstractSome regression models for analyzing relationships between random intervals (i.e., random variables taking intervals as outcomes) are presented. The proposed approaches are extensions of previous existing models and they account for cross relationships between midpoints and spreads (or radii) of the intervals in a unique equation based on the interval arithmetic. The estimation problem, which can be written as a constrained minimization problem, is theoretically analyzed and empirically tested. In addition, numerically stable general expressions of the estimators are provided. The main differences between the new and the existing methods are highlighted in a real-life application, where it is shown that the new model provides the most accurate results by preserving the coherency with the interval nature of the data.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofComputational Statisticsen_US
dc.rights© Springeren_US
dc.subjectInterval-valued dataen_US
dc.subjectLeast-squares estimatorsen_US
dc.subjectLinear modellingen_US
dc.subjectMultiple regressionen_US
dc.subjectSet arithmeticen_US
dc.titleMultiple linear regression models for random intervals: a set arithmetic approachen_US
dc.typeArticleen_US
dc.collaborationKorea Universityen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationUniversity of Oviedoen_US
dc.collaborationJustus Liebig University Gießenen_US
dc.collaborationQueen Mary University of Londonen_US
dc.subject.categoryEconomics and Businessen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryGermanyen_US
dc.countryUnited Kingdomen_US
dc.countrySpainen_US
dc.subject.fieldSocial Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1007/s00180-019-00910-1en_US
dc.identifier.scopus2-s2.0-85068228526en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85068228526en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.issue2en_US
dc.relation.volume35en_US
cut.common.academicyear2018-2019en_US
dc.identifier.spage755en_US
dc.identifier.epage773en_US
item.grantfulltextnone-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1en-
crisitem.journal.journalissn1613-9658-
crisitem.journal.publisherSpringer Nature-
crisitem.author.deptDepartment of Finance, Accounting and Management Science-
crisitem.author.facultyFaculty of Tourism Management, Hospitality and Entrepreneurship-
crisitem.author.orcid0000-0001-9704-9510-
crisitem.author.parentorgFaculty of Management and Economics-
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