LearnBayes (version 2.15.1)

discrete.bayes.2: Posterior distribution of two parameters with discrete priors

Description

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

Usage

discrete.bayes.2(df,prior,y=NULL,...)

Arguments

df

name of the function defining the sampling density of two parameters

prior

matrix defining the prior density; the row names and column names of the matrix define respectively the values of parameter 1 and values of parameter 2 and the entries of the matrix give the prior probabilities

y

y is a matrix of data values, where each row corresponds to a single observation

...

any further fixed parameter values used in the sampling density function

Value

prob

matrix of posterior probabilities

pred

scalar with prior predictive probability

Examples

# NOT RUN {
p1 = seq(0.1, 0.9, length = 9)
p2 = p1
prior = matrix(1/81, 9, 9)
dimnames(prior)[[1]] = p1
dimnames(prior)[[2]] = p2
discrete.bayes.2(twoproplike,prior)
# }