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Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57125
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dc.contributor.authorZheng Weien_US
dc.contributor.authorDaeyoung Kimen_US
dc.contributor.authorTonghui Wangen_US
dc.contributor.authorTeerawut Teetranonten_US
dc.date.accessioned2018-09-05T03:35:17Z-
dc.date.available2018-09-05T03:35:17Z-
dc.date.issued2017-02-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85012924695en_US
dc.identifier.other10.1007/978-3-319-50742-2_22en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012924695&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/57125-
dc.description.abstract© Springer International Publishing AG 2017. We introduce a class of multivariate non-exchangeable copulas which generalizes many known bivariate FGM type copula families. The properties such as moments, affiliation, association, and positive lower orthant dependent of the proposed class of copula are studied. The simple-to-use multiple regression function and multiple dependence measure formula for this new class of copulas are derived. Several examples are given to illustrate the main results obtained in this paper.en_US
dc.subjectComputer Scienceen_US
dc.titleA multivariate generalized FGM copulas and its application to multiple regressionen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume692en_US
article.stream.affiliationsUniversity of Massachusettsen_US
article.stream.affiliationsChiang Mai Universityen_US
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