Computes Posterior Probabilities for Discrete Models
Given a data table with columns Prior and Likelihood, computes posterior probabilities
bayesian_crank(d)
d
: data frame with columns Prior and Likelihooddata frame with new columns Product and Posterior
Jim Albert
df <- data.frame(p=c(.1, .3, .5, .7, .9), Prior=rep(1/5, 5)) y <- 5 n <- 10 df$Likelihood <- dbinom(y, prob=df$p, size=n) df <- bayesian_crank(df)