It takes a fitted SemiParBIVProbit,copulaReg,copulaSampleSel,SemiParTRIVProbit object produced by SemiParBIVProbit(),copulaReg(),copulaSampleSel(),SemiParTRIVProbit() and,
for each equation, produces predictions
for a new set of values of the model covariates or the original values used for the model fit.
Standard errors of predictions can be produced and are based on the posterior distribution of the model coefficients. This function is a
wrapper for predict.gam() in mgcv. Please see the documentation of predict.gam() for full details.
"predict"(object, eq, ...)copulaReg/copulaSampleSel object as
produced by SemiParBIVProbit()/copulaReg()/copulaSampleSel().predict.gam() in mgcv.type = "response" (which gives predictions on the scale of the response variable). For
the case of continuous responses this function will NOT produce correct predictions for the outcome variable (except for the Gaussian case). This
is because for all distributions (except the Gaussian) implemented in this package the distribution parameters
determine the mean and variance
through functions of them. SemiParBIVProbit, copulaReg, copulaSampleSel, plot.SemiParBIVProbit