discint

Computes a highest probability interval for a discrete probability
distribution

models

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.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

discint function

<dl> <dt>dist</dt>
<dd>probability distribution written as a matrix where
 the first column contain the values and the second column 
 the probabilities</dd> <dt>prob</dt>
<dd>probability content of interest</dd></dl>

Arguments

Author

Highest probability interval for a discrete distribution — discint

<dl>

 <dt>dist</dt>
<dd>probability distribution written as a matrix where
 the first column contain the values and the second column 
 the probabilities</dd>

 <dt>prob</dt>
<dd>probability content of interest</dd>

</dl>

discint: Highest probability interval for a discrete distribution

Description

Usage

Value

Arguments

Author

Examples