'Rcpp' Implementation of Dirichlet Process Regression R package RcppDPR version 0.1.10 '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. Software Imports: Rcpp (>= 1.0.13) LinkingTo: Rcpp, RcppArmadillo, RcppGSL Suggests: testthat (>= 3.0.0), snpStats Mohammad Abu Gazala <abugazalamohammad@gmail.com> Comprehensive R Archive Network (CRAN) Mohammad Abu Gazala [cre, aut], Daniel Nachun [ctb], Ping Zeng [ctb] GPL-3 2025-03-19 application/tgz https://CRAN.R-project.org/package=RcppDPR doi:10.32614/CRAN.package.RcppDPR