R/bicop_methods.R
predict_bicop.RdPredictions of the density, distribution function, h-functions (with their inverses) for a bivariate copula model.
a bicop object.
points where the fit shall be evaluated.
what to predict, one of "pdf", "cdf", "hfunc1", "hfunc2",
"hinv1", "hinv2".
unused.
fitted() can only be called if the model was fit with the
keep_data = TRUE option.
When at least one variable is discrete, more than two columns are required
for newdata: the first \(n \times 2\) block contains realizations of
\(F_{X_1}(x_1), F_{X_2}(x_2)\). The second \(n \times 2\) block contains
realizations of \(F_{X_1}(x_1^-), F_{X_1}(x_1^-)\). The minus indicates a
left-sided limit of the cdf. For, e.g., an integer-valued variable, it holds
\(F_{X_1}(x_1^-) = F_{X_1}(x_1 - 1)\). For continuous variables the left
limit and the cdf itself coincide. Respective columns can be omitted in the
second block.