RcppDPR: 'Rcpp' Implementation of Dirichlet Process Regression
'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 |
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 |
Documentation:
Downloads:
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