'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 <abugazalamohammad at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | RcppDPR results |
| Reference manual: | RcppDPR.html , RcppDPR.pdf |
| Package source: | RcppDPR_0.1.10.tar.gz |
| Windows binaries: | r-devel: RcppDPR_0.1.10.zip, r-release: RcppDPR_0.1.10.zip, r-oldrel: RcppDPR_0.1.10.zip |
| macOS binaries: | r-release (arm64): RcppDPR_0.1.10.tgz, r-oldrel (arm64): RcppDPR_0.1.10.tgz, r-release (x86_64): RcppDPR_0.1.10.tgz, r-oldrel (x86_64): RcppDPR_0.1.10.tgz |
| Old sources: | RcppDPR archive |
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