Sequential Monte Carlo without likelihoods Sisson, Scott en_US Fan, Yanan en_US Tanaka, Mark en_US 2021-11-25T13:26:22Z 2021-11-25T13:26:22Z 2007 en_US
dc.description.abstract Recent new methods in Bayesian simulation have provided ways of evaluating posterior distributions in the presence of analytically or computationally intractable likelihood functions. Despite representing a substantial methodological advance, existing methods based on rejection sampling or Markov chain Monte Carlo can be highly inefficient and accordingly require far more iterations than may be practical to implement. Here we propose a sequential Monte Carlo sampler that convincingly overcomes these inefficiencies. We demonstrate its implementation through an epidemiological study of the transmission rate of tuberculosis. en_US
dc.identifier.issn 0027-8424 en_US
dc.language English
dc.language.iso EN en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri en_US
dc.source Legacy MARC en_US
dc.subject.other approximate Bayesian computation en_US
dc.subject.other Bayesian inference en_US
dc.subject.other importance en_US
dc.subject.other sampling en_US
dc.subject.other intractable likelihoods en_US
dc.subject.other tuberculosis en_US
dc.title Sequential Monte Carlo without likelihoods en_US
dc.type Journal Article en
dcterms.accessRights metadata only access
dspace.entity.type Publication en_US
unsw.identifier.doiPublisher en_US
unsw.relation.faculty Science
unsw.relation.ispartofissue 6 en_US
unsw.relation.ispartofjournal Proceedings of the National Academy of Sciences of the United States of America en_US
unsw.relation.ispartofpagefrompageto 1760-1765 en_US
unsw.relation.ispartofvolume 104 en_US
unsw.relation.originalPublicationAffiliation Sisson, Scott, Mathematics & Statistics, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Fan, Yanan, Mathematics & Statistics, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Tanaka, Mark, Biotechnology & Biomolecular Sciences, Faculty of Science, UNSW en_US School of Mathematics & Statistics * School of Biotechnology & Biomolecular Sciences *
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