pdiscp

Computes predictive distribution for number of successes of
 future binomial experiment
 with a discrete distribution for the proportion.

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

pdiscp function

<dl> <dt>p</dt>
<dd>vector of proportion values</dd> <dt>probs</dt>
<dd>vector of probabilities</dd> <dt>n</dt>
<dd>size of future binomial sample</dd> <dt>s</dt>
<dd>vector of number of successes for future binomial experiment</dd></dl>

Arguments

Author

Predictive distribution for a binomial sample with a discrete prior — pdiscp

<dl>

 <dt>p</dt>
<dd>vector of proportion values</dd>

 <dt>probs</dt>
<dd>vector of probabilities</dd>

 <dt>n</dt>
<dd>size of future binomial sample</dd>

 <dt>s</dt>
<dd>vector of number of successes for future binomial experiment</dd>

</dl>

pdiscp: Predictive distribution for a binomial sample with a discrete prior

Description

Usage

Value

Arguments

Author

Examples