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Article: A unified method for checking compatibility and uniqueness for finite discrete conditional distributions

TitleA unified method for checking compatibility and uniqueness for finite discrete conditional distributions
Authors
Keywords2-norm
Box constraints
Compatibility
Gibbs sampler
Kullback-Leibler distance
Quadratic optimization with constraints
Issue Date2009
PublisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03610926.asp
Citation
Communications In Statistics - Theory And Methods, 2009, v. 38 n. 1, p. 115-129 How to Cite?
AbstractChecking compatibility for two given conditional distributions and identifying the corresponding unique compatible marginal distributions are important problems in mathematical statistics, especially in Bayesian inferences. In this article, we develop a unified method to check the compatibility and uniqueness for two finite discrete conditional distributions. By formulating the compatibility problem into a system of linear equations subject to constraints, it can be reduced to a quadratic optimization problem with box constraints. We also extend the proposed method from two-dimensional cases to higher-dimensional cases. Finally, we show that our method can be easily applied to checking compatibility and uniqueness for a regression function and a conditional distribution. Several numerical examples are used to illustrate the proposed method. Some comparisons with existing methods are also presented.
Persistent Identifierhttp://hdl.handle.net/10722/83067
ISSN
2015 Impact Factor: 0.3
2015 SCImago Journal Rankings: 0.518
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorTian, GLen_HK
dc.contributor.authorTan, Men_HK
dc.contributor.authorNg, KWen_HK
dc.contributor.authorTang, MLen_HK
dc.date.accessioned2010-09-06T08:36:32Z-
dc.date.available2010-09-06T08:36:32Z-
dc.date.issued2009en_HK
dc.identifier.citationCommunications In Statistics - Theory And Methods, 2009, v. 38 n. 1, p. 115-129en_HK
dc.identifier.issn0361-0926en_HK
dc.identifier.urihttp://hdl.handle.net/10722/83067-
dc.description.abstractChecking compatibility for two given conditional distributions and identifying the corresponding unique compatible marginal distributions are important problems in mathematical statistics, especially in Bayesian inferences. In this article, we develop a unified method to check the compatibility and uniqueness for two finite discrete conditional distributions. By formulating the compatibility problem into a system of linear equations subject to constraints, it can be reduced to a quadratic optimization problem with box constraints. We also extend the proposed method from two-dimensional cases to higher-dimensional cases. Finally, we show that our method can be easily applied to checking compatibility and uniqueness for a regression function and a conditional distribution. Several numerical examples are used to illustrate the proposed method. Some comparisons with existing methods are also presented.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03610926.aspen_HK
dc.relation.ispartofCommunications in Statistics - Theory and Methodsen_HK
dc.subject2-normen_HK
dc.subjectBox constraintsen_HK
dc.subjectCompatibilityen_HK
dc.subjectGibbs sampleren_HK
dc.subjectKullback-Leibler distanceen_HK
dc.subjectQuadratic optimization with constraintsen_HK
dc.titleA unified method for checking compatibility and uniqueness for finite discrete conditional distributionsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0361-0926&volume=38&issue=1&spage=115&epage=129.&date=2009&atitle=A+Unified+Method+for+Checking+Compatibility+and+Uniqueness+for+Finite+Discrete+Conditional+Distributionsen_HK
dc.identifier.emailTian, GL: gltian@hku.hken_HK
dc.identifier.emailNg, KW: kaing@hkucc.hku.hken_HK
dc.identifier.authorityTian, GL=rp00789en_HK
dc.identifier.authorityNg, KW=rp00765en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/03610920802169586en_HK
dc.identifier.scopuseid_2-s2.0-54349113563en_HK
dc.identifier.hkuros163567en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-54349113563&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume38en_HK
dc.identifier.issue1en_HK
dc.identifier.spage115en_HK
dc.identifier.epage129en_HK
dc.identifier.isiWOS:000260055000009-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridTian, GL=25621549400en_HK
dc.identifier.scopusauthoridTan, M=7401464906en_HK
dc.identifier.scopusauthoridNg, KW=7403178774en_HK
dc.identifier.scopusauthoridTang, ML=7401974011en_HK
dc.identifier.citeulike3427568-

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