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Article: Inversion of Bayes formula and measures of Bayesian information gain and pairwise dependence

TitleInversion of Bayes formula and measures of Bayesian information gain and pairwise dependence
Authors
KeywordsBayes formula
Bayesian information gain function
Information gain index
Inverse Bayes formula
Likelihood
Pairwise dependence index
Pairwise dependence measure ψ 2
Pearson's φ 2
Issue Date2011
PublisherInternational Press. The Journal's web site is located at http://www.intlpress.com/SII
Citation
Statistics And Its Interface, 2011, v. 4 n. 1, p. 95-103 How to Cite?
AbstractBy inverting the Bayes formula in a point-wise manner, we develop measures quantifying the information gained by the Bayesian process, in reference to the Fisher information. Simple examples are used for focused illustrations of the ideas. Numerical computation for the measures is discussed with formulae. By extending the information gain concept to the broader context of distribution theory, we arrive at a pairwise dependence measure, which can handle the case of functional dependence and becomes Pearson's φ 2 when the joint probability density function is defined.
Persistent Identifierhttp://hdl.handle.net/10722/133302
ISSN
2015 Impact Factor: 1.546
2015 SCImago Journal Rankings: 0.481
References

 

DC FieldValueLanguage
dc.contributor.authorNg, KWen_HK
dc.contributor.authorTong, Hen_HK
dc.date.accessioned2011-05-11T03:20:47Z-
dc.date.available2011-05-11T03:20:47Z-
dc.date.issued2011en_HK
dc.identifier.citationStatistics And Its Interface, 2011, v. 4 n. 1, p. 95-103en_HK
dc.identifier.issn1938-7989en_HK
dc.identifier.urihttp://hdl.handle.net/10722/133302-
dc.description.abstractBy inverting the Bayes formula in a point-wise manner, we develop measures quantifying the information gained by the Bayesian process, in reference to the Fisher information. Simple examples are used for focused illustrations of the ideas. Numerical computation for the measures is discussed with formulae. By extending the information gain concept to the broader context of distribution theory, we arrive at a pairwise dependence measure, which can handle the case of functional dependence and becomes Pearson's φ 2 when the joint probability density function is defined.en_HK
dc.languageeng-
dc.publisherInternational Press. The Journal's web site is located at http://www.intlpress.com/SIIen_HK
dc.relation.ispartofStatistics and its Interfaceen_HK
dc.rightsStatistics and Its Interface. Copyright © International Press.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBayes formulaen_HK
dc.subjectBayesian information gain functionen_HK
dc.subjectInformation gain indexen_HK
dc.subjectInverse Bayes formulaen_HK
dc.subjectLikelihooden_HK
dc.subjectPairwise dependence indexen_HK
dc.subjectPairwise dependence measure ψ 2en_HK
dc.subjectPearson's φ 2en_HK
dc.titleInversion of Bayes formula and measures of Bayesian information gain and pairwise dependenceen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1938-7989&volume=4&issue=1&spage=95&epage=103&date=2011&atitle=Inversion+of+Bayes+formula+and+measures+of+Bayesian+information+gain+and+pairwise+dependence-
dc.identifier.emailNg, KW: kaing@hkucc.hku.hken_HK
dc.identifier.authorityNg, KW=rp00765en_HK
dc.description.naturepostprint-
dc.identifier.scopuseid_2-s2.0-84864383095en_HK
dc.identifier.hkuros184788-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84864383095&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume4en_HK
dc.identifier.issue1en_HK
dc.identifier.spage95en_HK
dc.identifier.epage103en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridNg, KW=7403178774en_HK
dc.identifier.scopusauthoridTong, H=7201359749en_HK

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