discrete.bayes {LearnBayes} | R Documentation |
Computes the posterior distribution for an arbitrary one parameter distribution for a discrete prior distribution.
discrete.bayes(df,prior,y,...)
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 |
prob |
vector of posterior probabilities |
pred |
scalar with prior predictive probability |
Jim Albert
prior=c(.25,.25,.25,.25)
names(prior)=c(.2,.25,.3,.35)
y=5
n=10
discrete.bayes(dbinom,prior,y,size=n)