[ctb],
Giovanni Sighinolfi [ctb]Perform nonparametric Bayesian analysis using Dirichlet processes without the need to program the inference algorithms. Utilise included pre-built models or specify custom models and allow the 'dirichletprocess' package to handle the Markov chain Monte Carlo sampling. Our Dirichlet process objects can act as building blocks for a variety of statistical models including and not limited to: density estimation, clustering and prior distributions in hierarchical models. See Teh, Y. W. (2011) <https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, among many other sources.
| Version: | 0.4.0 |
| Depends: | R (≥ 2.10) |
| Imports: | gtools, ggplot2, mvtnorm |
| Suggests: | testthat, knitr, rmarkdown, tidyr, dplyr |
| Published: | 2020-06-13 |
| Author: | Gordon J. Ross [aut],
Dean Markwick [aut, cre],
Kees Mulder [ctb],
Giovanni Sighinolfi [ctb] |
| Maintainer: | Dean Markwick <dean.markwick at talk21.com> |
| BugReports: | https://github.com/dm13450/dirichletprocess/issues |
| License: | GPL-3 |
| URL: | https://github.com/dm13450/dirichletprocess |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | dirichletprocess results |
| Reference manual: | dirichletprocess.pdf |
| Vignettes: |
dirichletprocess: An R Package for Fitting Complex Bayesian Nonparametric Models |
| Package source: | dirichletprocess_0.4.0.tar.gz |
| Windows binaries: | r-devel: dirichletprocess_0.4.0.zip, r-release: dirichletprocess_0.4.0.zip, r-oldrel: dirichletprocess_0.4.0.zip |
| macOS binaries: | r-release: dirichletprocess_0.4.0.tgz, r-oldrel: dirichletprocess_0.4.0.tgz |
| Old sources: | dirichletprocess archive |
Please use the canonical form https://CRAN.R-project.org/package=dirichletprocess to link to this page.