copulaboost: Fitting Additive Copula Regression Models for Binary Outcome Regression

Additive copula regression for regression problems with binary outcome via gradient boosting [Brant, Hobæk Haff (2022); <doi:10.48550/arXiv.2208.04669>]. 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.

Version:	0.1.0
Imports:	rvinecopulib (≥ 0.5.4.1.0)
Published:	2022-08-23
DOI:	10.32614/CRAN.package.copulaboost
Author:	Simon Boge Brant [aut, cre], Ingrid Hobæk Haff [aut]
Maintainer:	Simon Boge Brant <simbrant91 at gmail.com>
License:	MIT + file LICENCE
NeedsCompilation:	no
CRAN checks:	copulaboost results

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