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MCMCpack: Markov chain Monte Carlo in R

dc.contributor.authorMartin, Andrew D.
dc.contributor.authorQuinn, Kevin M.
dc.contributor.authorPark, Jong Hee
dc.date.accessioned2015-12-04T15:39:13Z
dc.date.available2015-12-04T15:39:13Z
dc.date.issued2011-06
dc.identifier.citationAndrew D. Martin, Kevin M. Quinn, and Jong Hee Park. 2011. “MCMCpack: Markov chain Monte Carlo in R.” Journal of Statistical Software. 42(9): 1-21.en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/116099
dc.description.abstractWe introduce MCMCpack, an R package that contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. In addition to code that can be used to fit commonly used models, MCMCpack also contains some useful utility functions, including some additional density functions and pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization.en_US
dc.language.isoen_USen_US
dc.publisherFoundation for Open Access Statisticsen_US
dc.subjectBayesian inferenceen_US
dc.subjectMarkov chain Monte Carloen_US
dc.subjectRen_US
dc.titleMCMCpack: Markov chain Monte Carlo in Ren_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPolitical Science
dc.subject.hlbtoplevelSocial Sciences
dc.contributor.affiliationumLSA Dean's Officeen_US
dc.contributor.affiliationotherUniversity of California, Berkeleyen_US
dc.contributor.affiliationotherUniversity of Chicagoen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/116099/1/jstatSoft11a.pdf
dc.identifier.sourceJournal of Statistical Softwareen_US
dc.identifier.orcid0000-0002-6532-0721en_US
dc.identifier.name-orcidMartin, Andrew; 0000-0002-6532-0721en_US
dc.owningcollnamePolitical Science


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