Create Dirichlet process objects that can be used as infinite mixture models in a variety of ways. Some examples include; density estimation, Poisson process intensity inference, hierarchical modelling and clustering. See Teh, Y. W. (2011) <https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, among many other sources.
| Version: | 0.2.0 |
| Depends: | R (≥ 2.10) |
| Imports: | gtools, ggplot2, mvtnorm |
| Suggests: | testthat, knitr, rmarkdown, tidyr, dplyr |
| Published: | 2018-01-29 |
| Author: | Dean Markwick [aut, cre], Gordon J. Ross [aut] |
| 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_0.2.0.tar.gz |
| Windows binaries: | r-devel: dirichletprocess_0.2.0.zip, r-release: dirichletprocess_0.2.0.zip, r-oldrel: dirichletprocess_0.2.0.zip |
| OS X El Capitan binaries: | r-release: dirichletprocess_0.2.0.tgz |
| OS X Mavericks binaries: | r-oldrel: not available |
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