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Article: Multivariate zero-and-one inflated Poisson model with applications

TitleMultivariate zero-and-one inflated Poisson model with applications
Authors
KeywordsExpectation–maximization (EM) algorithm
Multivariate zero-and-one inflated poisson
Univariate zero-and-one inflated poisson
Zero-inflated poisson
Issue Date2020
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cam
Citation
Journal of Computational and Applied Mathematics, 2020, v. 365, article no. 112356 How to Cite?
AbstractThis paper extends the univariate zero-and-one inflated Poisson (ZOIP) distribution (Melkersson & Olsson, 1999; Zhang et al., 2016) to its multivariate version, which can be used to model correlated multivariate count data with large proportions of zeros and ones marginally. More importantly, this new multivariate ZOIP distribution possesses a flexible dependency structure; i.e., the correlation coefficient between any two random components could be either positive or negative depending on the values of the parameters. The important distributional properties are explored and some useful statistical inference methods without and with covariates are developed. Simulation studies are conducted to evaluate the performance of the proposed methods. Finally, two real data sets on healthcare and insurance are used to illustrate the proposed methods. © 2019 Elsevier B.V.
Persistent Identifierhttp://hdl.handle.net/10722/272966
ISSN
2019 Impact Factor: 2.037
2015 SCImago Journal Rankings: 1.089

 

DC FieldValueLanguage
dc.contributor.authorZhang, C-
dc.contributor.authorTian, G-
dc.contributor.authorYuen, KC-
dc.contributor.authorWu, Q-
dc.contributor.authorLi, T-
dc.date.accessioned2019-08-06T09:20:02Z-
dc.date.available2019-08-06T09:20:02Z-
dc.date.issued2020-
dc.identifier.citationJournal of Computational and Applied Mathematics, 2020, v. 365, article no. 112356-
dc.identifier.issn0377-0427-
dc.identifier.urihttp://hdl.handle.net/10722/272966-
dc.description.abstractThis paper extends the univariate zero-and-one inflated Poisson (ZOIP) distribution (Melkersson & Olsson, 1999; Zhang et al., 2016) to its multivariate version, which can be used to model correlated multivariate count data with large proportions of zeros and ones marginally. More importantly, this new multivariate ZOIP distribution possesses a flexible dependency structure; i.e., the correlation coefficient between any two random components could be either positive or negative depending on the values of the parameters. The important distributional properties are explored and some useful statistical inference methods without and with covariates are developed. Simulation studies are conducted to evaluate the performance of the proposed methods. Finally, two real data sets on healthcare and insurance are used to illustrate the proposed methods. © 2019 Elsevier B.V.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cam-
dc.relation.ispartofJournal of Computational and Applied Mathematics-
dc.subjectExpectation–maximization (EM) algorithm-
dc.subjectMultivariate zero-and-one inflated poisson-
dc.subjectUnivariate zero-and-one inflated poisson-
dc.subjectZero-inflated poisson-
dc.titleMultivariate zero-and-one inflated Poisson model with applications-
dc.typeArticle-
dc.identifier.emailYuen, KC: kcyuen@hku.hk-
dc.identifier.authorityYuen, KC=rp00836-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.cam.2019.112356-
dc.identifier.scopuseid_2-s2.0-85069936730-
dc.identifier.hkuros299776-
dc.identifier.volume365-
dc.identifier.spagearticle no. 112356-
dc.identifier.epagearticle no. 112356-
dc.publisher.placeNetherlands-

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