The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Basic implementation of a Gibbs sampler for a Chinese Restaurant Process along with some visual aids to help understand how the sampling works. This is developed as part of a postgraduate school project for an Advanced Bayesian Nonparametric course. It is inspired by Tamara Broderick's presentation on Nonparametric Bayesian statistics given at the Simons institute.
Version: | 0.0.1 |
Imports: | mvtnorm, progress |
Published: | 2021-11-29 |
DOI: | 10.32614/CRAN.package.nonparametric.bayes |
Author: | Erik-Cristian Seulean [aut, cre] |
Maintainer: | Erik-Cristian Seulean <erikseulean at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | nonparametric.bayes results |
Reference manual: | nonparametric.bayes.pdf |
Package source: | nonparametric.bayes_0.0.1.tar.gz |
Windows binaries: | r-devel: nonparametric.bayes_0.0.1.zip, r-release: nonparametric.bayes_0.0.1.zip, r-oldrel: nonparametric.bayes_0.0.1.zip |
macOS binaries: | r-release (arm64): nonparametric.bayes_0.0.1.tgz, r-oldrel (arm64): nonparametric.bayes_0.0.1.tgz, r-release (x86_64): nonparametric.bayes_0.0.1.tgz, r-oldrel (x86_64): nonparametric.bayes_0.0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=nonparametric.bayes to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.