ZIPGUI: Bayes estimation of a zero inflated Poisson (ZIP) model

In BfRstats/rriskBayes2: Predefined Bayes models fitted with Markov chain Monte Carlo (MCMC) (related to the 'rrisk' project)

Description

This function provides a GUI for the function rrisk.BayesZIP.

Usage

ZIPGUI(data=NULL, prior.lambda=c(1,10), prior.pi=c(0.8,1),
 chains=3, burn=1000, update=10000, thin=1)

Arguments

data	A vector of numeric data, containing zeros, and of minimal length 10.
prior.lambda	Numeric vector containing minimum and maximum of a uniform distribution used as prior for the Poisson parameter lambda, e.g., lambda ~ prior.lambda(*,*)=unif(*,*).
prior.pi	Numeric vector containing parameters of a beta distribution describing prior knowledge about prevalence (proportion of contaminated samples), e.g., pi ~ prior.pi(*,*)=beta(*,*).
chains	Positive single numeric value, number of independent MCMC chains (default 3).
burn	Positive single numeric value, length of the burn-in period (default 1000).
update	Positive single numeric value, length of update iterations for estimation (default 10000).
thin	Positive single numeric value (default 1). The samples from every kth iteration will be used for inference, where k is the value of thin. Setting thin > 1 can help to reduce the autocorrelation in the sample.

Value

The function ZIPGUI returns an instance of the bayesmodelClass class containing following information

convergence	Logical, whether the model has converged (assessed by the user).
results	Data frame containing statitsics of the posterior distribution.
jointpost	Data frame giving the joint posterior probability distribution.
nodes	Names of the parameters jointly estimated by the Bayes model.
model	Model in rjags/JAGS (originally BRugs/Winbugs) syntax as a character string.
chains	Number of independent MCMC chains.
burn	Length of burn-in period.
update	Length of update iterations for estimation.

Note

The convergence of the model will be entered by the user after the simulation process.

References

Bohning, D., E. Dietz, P. Schlattman, L. Mendonca, and U. Kirchner (1999). The zero-inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology. Journal of the Royal Statistical Society, Series A 162, 195-209.

See Also

rrisk.BayesZIP

Examples

data <- rpois(30, 4)
ZIPGUI(data)

BfRstats/rriskBayes2 documentation built on May 5, 2019, 2:42 p.m.