predicting with zoib models (MCMC / RJags)

Question

I am using the zoib package in R to build zero-inflated beta regression models. I am looking for a simple way to use the models that zoib produces to calculate a predicted response for a new dataset. By "new dataset" I mean data not used to build the original zoib models.

I know I can just take the zoib model parameters and manually write a function in R to predict with but I want to utilise the fact that zoib models are Bayesian so I can get a posterior distribution of possible response values. My plan is to use the posterior distributions to calculate confidence intervals around each prediction.

Because zoib uses a MCMC approach within RJags I have investigated these two solutions:

1. manipulating the code within RJags

2. appending the new data with an "NA" response variable

The first solution I don't know how to implement because zoib runs RJags internally and the zero-inflated model it runs is very complicated. I tried the second solution but it just ignored the rows of data that I appended with "NA" response values.

Answer 1

I emailed the zoib package developers and this was there response.

For now, the zoib function can only output posterior predictive samples for Y given the X in the data set where the zoib regression is applied to, but not for a new set of X's. Your suggestion can be easily incorporated into the new version of the package, which is expected to be out in about a few weeks.