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Article: Bayesian inference for a stochastic epidemic model with uncertain numbers of susceptibles of several types

TitleBayesian inference for a stochastic epidemic model with uncertain numbers of susceptibles of several types
Authors
KeywordsBayesian inference
Epidemic
Gibbs sampler
Markov chain Monte Carlo methods
Metropolis-Hastings algorithm
Issue Date2003
PublisherBlackwell Publishing Asia. The Journal's web site is located at http://www.blackwellpublishing.com/journals/ANZS
Citation
Australian And New Zealand Journal Of Statistics, 2003, v. 45 n. 4, p. 491-502 How to Cite?
AbstractA stochastic epidemic model with several kinds of susceptible is used to analyse temporal disease outbreak data from a Bayesian perspective. Prior distributions are used to model uncertainty in the actual numbers of susceptibles initially present. The posterior distribution of the parameters of the model is explored via Markov chain Monte Carlo methods. The methods are illustrated using two datasets, and the results are compared where possible to results obtained by previous analyses.
Persistent Identifierhttp://hdl.handle.net/10722/82974
ISSN
2015 Impact Factor: 0.431
2015 SCImago Journal Rankings: 0.275
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHayakawa, Yen_HK
dc.contributor.authorO'Neill, PDen_HK
dc.contributor.authorUpton, Den_HK
dc.contributor.authorYip, PSFen_HK
dc.date.accessioned2010-09-06T08:35:30Z-
dc.date.available2010-09-06T08:35:30Z-
dc.date.issued2003en_HK
dc.identifier.citationAustralian And New Zealand Journal Of Statistics, 2003, v. 45 n. 4, p. 491-502en_HK
dc.identifier.issn1369-1473en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82974-
dc.description.abstractA stochastic epidemic model with several kinds of susceptible is used to analyse temporal disease outbreak data from a Bayesian perspective. Prior distributions are used to model uncertainty in the actual numbers of susceptibles initially present. The posterior distribution of the parameters of the model is explored via Markov chain Monte Carlo methods. The methods are illustrated using two datasets, and the results are compared where possible to results obtained by previous analyses.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Asia. The Journal's web site is located at http://www.blackwellpublishing.com/journals/ANZSen_HK
dc.relation.ispartofAustralian and New Zealand Journal of Statisticsen_HK
dc.subjectBayesian inferenceen_HK
dc.subjectEpidemicen_HK
dc.subjectGibbs sampleren_HK
dc.subjectMarkov chain Monte Carlo methodsen_HK
dc.subjectMetropolis-Hastings algorithmen_HK
dc.titleBayesian inference for a stochastic epidemic model with uncertain numbers of susceptibles of several typesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1369-1473&volume=45&issue=4&spage=491&epage=502&date=2003&atitle=Bayesian+inference+for+a+stochastic+epidemic+model+with+uncertain+numbers+of+susceptibles+of+several+typesen_HK
dc.identifier.emailYip, PSF: sfpyip@hku.hken_HK
dc.identifier.authorityYip, PSF=rp00596en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/1467-842X.00300-
dc.identifier.scopuseid_2-s2.0-0344153844en_HK
dc.identifier.hkuros94262en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0344153844&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume45en_HK
dc.identifier.issue4en_HK
dc.identifier.spage491en_HK
dc.identifier.epage502en_HK
dc.identifier.isiWOS:000186896900010-
dc.publisher.placeAustraliaen_HK
dc.identifier.scopusauthoridHayakawa, Y=7201356213en_HK
dc.identifier.scopusauthoridO'Neill, PD=7201735452en_HK
dc.identifier.scopusauthoridUpton, D=7005679083en_HK
dc.identifier.scopusauthoridYip, PSF=7102503720en_HK

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