R: Computes the posterior for binomial sampling and a mixture of...

binomial.beta.mix {LearnBayes} | R Documentation

## Computes the posterior for binomial sampling and a mixture of betas prior

### Description

Computes the parameters and mixing probabilities for a binomial sampling problem where the prior is a discrete mixture of beta densities.

### Usage

    binomial.beta.mix(probs,betapar,data)

### Arguments

`probs` | vector of probabilities of the beta components of the prior
`betapar` | matrix where each row contains the shape parameters for a beta component of the prior
`data` | vector of number of successes and number of failures

### Value

`probs` | vector of probabilities of the beta components of the posterior
`betapar` | matrix where each row contains the shape parameters for a beta component of the posterior

### Author(s)

Jim Albert

### Examples

    probs=c(.5, .5)
    beta.par1=c(15,5)
    beta.par2=c(10,10)
    betapar=rbind(beta.par1,beta.par2)
    data=c(20,15)
    binomial.beta.mix(probs,betapar,data)

[Package LearnBayes version 2.15 Index]