Antithetic Acceleration of Monte Carlo Integration in Bayesian Inference

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dc.contributor.author Geweke, John en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:26:22Z
dc.date.available 2011-02-07T06:26:22Z
dc.date.issued 1988 en_US
dc.identifier 2008008349 en_US
dc.identifier.citation Geweke John 1988, 'Antithetic Acceleration of Monte Carlo Integration in Bayesian Inference', Elsevier Science Publishers B.V., vol. 38, no. 1-2, pp. 73-90. en_US
dc.identifier.issn 0304-4076 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13961
dc.description.abstract It is proposed to sample antithetically rather than randomly from the posterior density in Bayesian inference using Monte Carlo integration. Conditions are established under which the number of replications required with antithetic sampling relative to the number required with random sampling is inversely proportional to sample size, as sample size increases. The result is illustrated in an experiment using a bivariate vector autoregression. en_US
dc.language en_US
dc.publisher Elsevier Science Publishers B.V. en_US
dc.relation.isbasedon http://dx.doi.org/10.1016/0304-4076(88)90027-9 en_US
dc.title Antithetic Acceleration of Monte Carlo Integration in Bayesian Inference en_US
dc.parent Journal of Econometrics en_US
dc.journal.volume 38 en_US
dc.journal.number 1-2 en_US
dc.publocation Amsterdam, The Netherlands en_US
dc.identifier.startpage 73 en_US
dc.identifier.endpage 90 en_US
dc.cauo.name BUS.Faculty of Business en_US
dc.conference Verified OK en_US
dc.for 140302 en_US
dc.personcode 101228 en_US
dc.percentage 100 en_US
dc.classification.name Econometric and Statistical Methods en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
dc.staffid 101228 en_US


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