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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("LearnBayes")

2.15.1 by Jim Albert, 2 years ago


Browse source code at https://github.com/cran/LearnBayes


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, weibulltools.

Depended on by TeachBayes, bayeslongitudinal, psbcGroup.

Suggested by mistat.


See at CRAN