summarize_gamma_poisson {bayesrules} | R Documentation |
Consider a Gamma-Poisson Bayesian model for rate parameter \lambda
with
a Gamma(shape, rate) prior on \lambda
and a Poisson likelihood for the data.
Given information on the prior (shape and rate)
and data (the sample size n and sum_y),
this function summarizes the mean, mode, and variance of the
prior and posterior Gamma models of \lambda
.
summarize_gamma_poisson(shape, rate, sum_y = NULL, n = NULL)
shape |
positive shape parameter of the Gamma prior |
rate |
positive rate parameter of the Gamma prior |
sum_y |
sum of observed data values for the Poisson likelihood |
n |
number of observations for the Poisson likelihood |
data frame
summarize_gamma_poisson(shape = 3, rate = 4, sum_y = 7, n = 12)