Functions for Learning Bayesian Inference

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.


Reference manual

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2.15.1 by Jim Albert, 4 years ago

Browse source code at

Authors: Jim Albert

Documentation:   PDF Manual  

Task views: Bayesian Inference, Probability Distributions, Survival Analysis, Teaching Statistics

GPL (>= 2) license

Imported by RSSampling, cancerTiming, evidence, spatialreg, spdep.

Depended on by ProbBayes, bayeslongitudinal, psbcGroup.

Suggested by mistat.

See at CRAN