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


Reference manual: copulaboost.pdf


Package source: copulaboost_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): copulaboost_0.1.0.tgz, r-oldrel (arm64): copulaboost_0.1.0.tgz, r-release (x86_64): copulaboost_0.1.0.tgz, r-oldrel (x86_64): copulaboost_0.1.0.tgz


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