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

Fifteen differences of the heights of cross and self fertilized plants quoted by
Fisher (1960)

A data frame with 15 observations on the following 1 variable.

<dl>
<dt>difference</dt>
<dd>
difference of heights of two types of plants
</dd>
</dl>

Fisher, R. (1960), Statistical Methods for Research Workers,
Edinburgh: Oliver and Boyd.

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

darwin

Description

Usage

Format

Source

LearnBayes

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