Nothing
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.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Mohammad Abu Gazala [cre, aut], Daniel Nachun [ctb], Ping Zeng [ctb] |
| Maintainer | Mohammad Abu Gazala <abugazalamohammad@gmail.com> |
| License | GPL-3 |
| Version | 0.1.10 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the RcppDPR package in your browser
Any scripts or data that you put into this service are public.
