LearnBayes: poisson.gamma.mix – R documentation

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poisson.gamma.mix

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)

LearnBayes

Functions for Learning Bayesian Inference

v2.15.1

GPL (>= 2)

Authors