R: Posterior distribution with discrete priors

discrete.bayes {LearnBayes} | R Documentation

## Posterior distribution with discrete priors

### Description

Computes the posterior distribution for an arbitrary one parameter distribution for a discrete prior distribution.

### Usage

    discrete.bayes(df,prior,y,...)

### Arguments

`df` | name of the function defining the sampling density
`prior` | vector defining the prior density; names of the vector define the parameter values and entries of the vector define the prior probabilities
`y` | vector of data values
`...` | any further fixed parameter values used in the sampling density function

### Value

`prob` | vector of posterior probabilities
`pred` | scalar with prior predictive probability

### Author(s)

Jim Albert

### Examples

    prior=c(.25,.25,.25,.25)
    names(prior)=c(.2,.25,.3,.35)
    y=5
    n=10
    discrete.bayes(dbinom,prior,y,size=n)

[Package LearnBayes version 2.15 Index]