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LaplacesDemon: a complete environment for Bayesian inference within R

Our presenter, Byron Hall,is the author of the freely contributed R package: LaplacesDemon. LaplacesDemon is a complete environment for Bayesian inference within R. LaplacesDemon offers over twenty MCMC algorithms, Laplace Approximation with multiple optimization algorithms, PMC, over 80 examples in the ?Examples? vignette, dozens of additional probability distributions, numerous MCMC diagnostics, Bayes factors, posterior predictive checks, a variety of plots, elicitation, parameter and variable importance, Bayesian forms of test statistics (such as Durbin-Watson, Jarque-Bera, etc.), validation, and much more.

Byron is president of Statisticat, LLC., a small statistical consulting firm that specializes in Bayesian inference (www.bayesian-inference.com).

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  • Mike S.

    Advanced for me (a non statistician) ... but inspiring! Great presentation and discussion. I appreciate that Byron Hall took the time to journey down and present to the group. He also shifted gears mid-stream to make some of the material more accessible to the broader audience.

    February 2, 2013

  • Dan P.

    Great topic with a diverse group, perhaps a bit much for non statisticians, but for statisticians excellent.

    January 29, 2013

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