Fitting Additive Copula Regression Models for Binary Outcome
Regression
Description
Additive copula regression for regression
problems with binary outcome via gradient boosting
[Brant, Hobæk Haff (2022); ]. The fitting process
includes a specialised model selection algorithm for each component, where
each component is found (by greedy optimisation) among all the D-vines with
only Gaussian pair-copulas of a fixed dimension, as specified by the user.
When the variables and structure have been selected, the algorithm then
re-fits the component where the pair-copula distributions can be different
from Gaussian, if specified.