Posterior predictive and univariate conditional posterior predictive distributions, currently implemented only for Gaussian copula models. If resp.var is not NA, returns an estimate of the conditional cdf at every observed data point for each MCMC iterate. If resp.var is NA, returns draws from the joint posterior predictive.
1 2 3 
object 

resp.var 
Either a character vector (length 1) with name of the response variable for conditional, or NA for draws from the joint posterior predictive. 
cond.vars 
Conditioning variables; either a list like list(X1=val1, X2=val2) with X1, X2 variables in the original data frame, or a P length vector with either the conditioning value or NA (for marginalized variables). Ignored if resp.var is NA 
numeric.as.factor 
Treat numeric variables as ordinal when conditioning 
... 
Ignored 
A matrix where each row is either a sample of the conditional posterior predictive cdf at each datapoint, or a single sample from the joint posterior predictive.
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs with the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.