Posterior distribution of two parameters with discrete priors
Computes the posterior distribution for an arbitrary two parameter distribution for a discrete prior distribution.
discrete.bayes.2(df,prior,y=NULL,...)
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 |
prob |
matrix of posterior probabilities |
pred |
scalar with prior predictive probability |
Jim Albert
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)
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