RcppDPR: 'Rcpp' Implementation of Dirichlet Process Regression (original) (raw)
'Rcpp' reimplementation of the the Bayesian non-parametric Dirichlet Process Regression model for penalized regression first published in Zeng and Zhou (2017) <doi:10.1038/s41467-017-00470-2>. A full Bayesian version is implemented with Gibbs sampling, as well as a faster but less accurate variational Bayes approximation.
| Version: | 0.1.10 |
|---|---|
| Imports: | Rcpp (≥ 1.0.13) |
| LinkingTo: | Rcpp, RcppArmadillo, RcppGSL |
| Suggests: | testthat (≥ 3.0.0), snpStats |
| Published: | 2025-03-19 |
| DOI: | 10.32614/CRAN.package.RcppDPR |
| Author: | Mohammad Abu Gazala [cre, aut], Daniel Nachun [ctb], Ping Zeng [ctb] |
| Maintainer: | Mohammad Abu Gazala |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | RcppDPR results |
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