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.

Functions for Learning Bayesian Inference

package-ubuntu-20.04-r-4.0.5#cran#LearnBayes-2.15.1

Running times in minutes for twenty male runners between the ages 20 and 29
who ran the New York Marathon.

A data frame with 20 observations on the following 1 variable.

<dl>
<dt>time</dt>
<dd>
running time
</dd>
</dl>

package-ubuntu-20.04-r-4.0.5#cran#LearnBayes-2.15.1#docs#marathontimes

marathontimes

Description

Usage

Format

Source

LearnBayes

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