poisson.gamma.mix {LearnBayes} | R Documentation |
Computes the posterior for Poisson sampling and a mixture of gammas prior
Description
Computes the parameters and mixing probabilities for a Poisson sampling problem where the prior is a discrete mixture of gamma densities.
Usage
poisson.gamma.mix(probs,gammapar,data)
Arguments
probs |
vector of probabilities of the gamma components of the prior |
gammapar |
matrix where each row contains the shape and rate parameters for a gamma component of the prior |
data |
list with components y, vector of counts, and t, vector of time intervals |
Value
probs |
vector of probabilities of the gamma components of the posterior |
gammapar |
matrix where each row contains the shape and rate parameters for a gamma component of the posterior |
Author(s)
Jim Albert
Examples
probs=c(.5, .5)
gamma.par1=c(1,1)
gamma.par2=c(10,2)
gammapar=rbind(gamma.par1,gamma.par2)
y=c(1,3,2,4,10); t=c(1,1,1,1,1)
data=list(y=y,t=t)
poisson.gamma.mix(probs,gammapar,data)
[Package LearnBayes version 2.15.1 Index]