| summarize_gamma_poisson {bayesrules} | R Documentation | 
Summarize the Gamma-Poisson Model
Description
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.
Usage
summarize_gamma_poisson(shape, rate, sum_y = NULL, n = NULL)
Arguments
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  | 
Value
data frame
Examples
summarize_gamma_poisson(shape = 3, rate = 4, sum_y = 7, n = 12)
[Package bayesrules version 0.0.2 Index]