LearnBayes (version 2.15.2)

discrete.bayes: 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,...)

Value

prob

vector of posterior probabilities

pred

scalar with prior predictive probability

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

Author

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)