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.
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Package source: |
RcppDPR_0.1.9.tar.gz |
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r-devel: RcppDPR_0.1.9.zip, r-release: not available, r-oldrel: not available |
macOS binaries: |
r-devel (arm64): not available, r-release (arm64): not available, r-oldrel (arm64): not available, r-devel (x86_64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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