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

Number of goals scored by a single professional soccer team
during the 2006 Major League Soccer season

A data frame with 35 observations on the following 1 variable.

<dl>
<dt>goals</dt>
<dd>
number of goals scored
</dd>
</dl>

Collected by author from the www.espn.com website.

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

soccergoals

Description

Usage

Format

Source

LearnBayes

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