Package: RcppDPR 0.1.10
Mohammad Abu Gazala
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.
Authors:
RcppDPR_0.1.10.tar.gz
RcppDPR_0.1.10.tar.gz(r-4.7-arm64)RcppDPR_0.1.10.tar.gz(r-4.7-x86_64)RcppDPR_0.1.10.tar.gz(r-4.6-arm64)RcppDPR_0.1.10.tar.gz(r-4.6-x86_64)
RcppDPR_0.1.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RcppDPR/json (API)
NEWS
| # Install 'RcppDPR' in R: |
| install.packages('RcppDPR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:99be1f5316. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 271 | ||
| linux-devel-x86_64 | OK | 315 | ||
| source / vignettes | OK | 239 | ||
| linux-release-arm64 | OK | 286 | ||
| linux-release-x86_64 | OK | 318 | ||
| wasm-release | OK | 147 |
Exports:fit_model
Dependencies:RcppRcppArmadilloRcppGSL
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit Dirichlet Process Regression model | fit_model |
| Use a DPR model to predict results from new data | predict.DPR_Model |