Package: copulaboost 0.1.0
Simon Boge Brant
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.
Authors:
copulaboost_0.1.0.tar.gz
copulaboost_0.1.0.tar.gz(r-4.5-noble)copulaboost_0.1.0.tar.gz(r-4.4-noble)
copulaboost_0.1.0.tgz(r-4.4-emscripten)copulaboost_0.1.0.tgz(r-4.3-emscripten)
copulaboost.pdf |copulaboost.html✨
copulaboost/json (API)
| # Install 'copulaboost' in R: |
| install.packages('copulaboost', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:f23f46a2b4. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-linux | OK | Nov 17 2024 |
Exports:copulaboostcopulareg
Dependencies:assertthatBHkde1dlatticerandtoolboxRcppRcppEigenRcppThreadrngWELLrvinecopulibwdm
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| copulaboost | copulaboost |
| copulareg | copulareg |
| predict.copulaboost | predict.copulaboost |
| predict.copulareg | predict.copulareg |