Build Dirichlet Process Objects for Bayesian Modelling
Overview
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.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Dean Markwick <dean.markwick@talk21.com>’
Found the following (possibly) invalid file URIs:
URI: Gordon.Ross@ed.ac.uk
From: inst/doc/dirichletprocess.pdf
URI: dean.markwick.15@ucl.ac.uk
From: inst/doc/dirichletprocess.pdf- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 57includes a package overview page
- Examples that run
- 100%11 run in a plain check
- Exported functions with examples
- 19%
- Documented parameters
- 100%
- Return-value docs
- 77%
- Help pages citing references
- 7%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 1
- Median days to close, 50 most recently updated closed PRs
- 4
Stars over time
Forks over time
Releases over time
Issues over time
PRs over time
Commits over time
10 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/dm13450/dirichletprocess on 2026-10-11.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
Show all practicesHide 1 practice
Dependencies
Installing dirichletprocess adds 19 packages (9 with compiled code, 15 MB of source tarballs). Heaviest: ggplot2 6.0 MB, isoband 1.5 MB, farver 1.2 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.4.2Latest
- RR 4.3.0 released · 2023-04-21
- 0.4.12023-03-10 · diff ↗ ·
added 3 exports
DirichletProcessGaussianFixedVariance, GaussianFixedVarianceMixtureCreate, PriorClusters - RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.4.02020-06-13 · diff ↗ ·
added 3 exports
DirichletProcessHierarchicalMvnormal2, HierarchicalMvnormal2Create, true_cluster_labels - RR 4.0.0 released · 2020-04-24
- 0.3.1.12020-04-03 · diff ↗
- 0.3.12019-12-11 · diff ↗
- 0.3.02019-05-03 · diff ↗ ·
added 11 exports
AlphaPriorPosteriorPlot, AlphaTraceplot, BetaMixture2Create, Burn, ClusterTraceplot, DiagnosticPlots, DirichletHMMCreate, DirichletProcessBeta2, LikelihoodTraceplot, PenalisedLikelihood, UpdateAlphaBeta - RR 3.6.0 released · 2019-04-26
- 0.2.22018-11-23 · diff ↗ ·
added 6 exports
DirichletProcessMvnormal2, LikelihoodDP, Mvnormal2Create, PosteriorFrame, plot_dirichletprocess_multivariate, plot_dirichletprocess_univariate - RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-01-29
- Total releases
- 9 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 0.2 KB / 1 file
- Download size
- 1.0 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("dirichletprocess")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.