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); <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 |
| 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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