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dirichletprocess  

Build Dirichlet Process Objects for Bayesian Modelling
View on CRAN: Click here


Download and install dirichletprocess package within the R console
Install from CRAN:
install.packages("dirichletprocess")

Install from Github:
library("remotes")
install_github("cran/dirichletprocess")

Install by package version:
library("remotes")
install_version("dirichletprocess", "0.4.2")



Attach the package and use:
library("dirichletprocess")
Maintained by
Dean Markwick
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-01-29
Latest Update: 2023-08-25
Description:
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) , among many other sources.
How to cite:
Dean Markwick (2018). dirichletprocess: Build Dirichlet Process Objects for Bayesian Modelling. R package version 0.4.2, https://cran.r-project.org/web/packages/dirichletprocess. Accessed 29 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:32), 0.2.0 (2018-01-29 19:24), 0.2.1 (2018-04-18 18:36), 0.2.2 (2018-11-23 18:50), 0.3.0 (2019-05-03 18:10), 0.3.1.1 (2020-04-03 08:49), 0.3.1 (2019-12-11 09:10), 0.4.0 (2020-06-13 12:40), 0.4.1 (2023-03-10 12:50)
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Other R packages that dirichletprocess depends, imports, suggests or enhances
Complete documentation for dirichletprocess
Functions, R codes and Examples using the dirichletprocess R package
Some associated functions: BetaMixture2Create . BetaMixtureCreate . Burn . ChangeObservations . ClusterComponentUpdate . ClusterLabelPredict . ClusterParameterUpdate . DiagnosticPlots . DirichletHMMCreate . DirichletProcessBeta . DirichletProcessBeta2 . DirichletProcessCreate . DirichletProcessExponential . DirichletProcessGaussian . DirichletProcessGaussianFixedVariance . DirichletProcessHierarchicalBeta . DirichletProcessHierarchicalMvnormal2 . DirichletProcessMvnormal . DirichletProcessMvnormal2 . DirichletProcessWeibull . ExponentialMixtureCreate . Fit.markov . Fit . GaussianFixedVarianceMixtureCreate . GaussianMixtureCreate . GlobalParameterUpdate . HierarchicalBetaCreate . HierarchicalMvnormal2Create . Initialise . Likelihood . LikelihoodDP . LikelihoodFunction . MixingDistribution . Mvnormal2Create . MvnormalCreate . PenalisedLikelihood . PosteriorClusters . PosteriorDraw . PosteriorFrame . PosteriorFunction . PosteriorParameters . Predictive . PriorClusters . PriorDensity . PriorDraw . PriorFunction . PriorParametersUpdate . StickBreaking . UpdateAlpha . UpdateAlphaBeta . WeibullMixtureCreate . dirichletprocess . plot.dirichletprocess . print.dirichletprocess . rats . true_cluster_labels . weighted_function_generator . 
Some associated R codes: beta_uniform_gamma.R . beta_uniform_pareto.R . burn.R . change_observations.R . cluster_component_update.R . cluster_label_change.R . cluster_label_predict.R . cluster_parameter_update.R . data.R . diagnostic_plots.R . dirichlet_hmm_create.R . dirichlet_process_beta.R . dirichlet_process_beta_2.R . dirichlet_process_create.R . dirichlet_process_exponential.R . dirichlet_process_gaussian.R . dirichlet_process_gaussian_fixed_variance.R . dirichlet_process_hierarchical_beta.R . dirichlet_process_hierarchical_mvnormal2.R . dirichlet_process_mvnormal.R . dirichlet_process_mvnormal2.R . dirichlet_process_weibull.R . dirichletprocess.R . duplicate_cluster_remove.R . exponential_gamma.R . fit.R . fit_hmm.R . global_parameter_update.R . hierarchical_beta.R . hierarchical_mvnormal2.R . initialise.R . likelihood.R . likelihood_function.R . metropolis_hastings.R . mixing_distribution.R . mixing_distribution_likelihood.R . mixing_distribution_penalised_likelihood.R . mixing_distribution_posterior_draw.R . mixing_distribution_posterior_parameters.R . mixing_distribution_predictive.R . mixing_distribution_prior_density.R . mixing_distribution_prior_draw.R . mixing_distribution_update_prior_parameters.R . mvnormal_normal_wishart.R . mvnormal_semi_conjugate.R . normal_fixed_variance.R . normal_inverse_gamma.R . plot.R . plot_dirichletprocess.R . posterior.R . posterior_clusters.R . posterior_frame.R . print.R . prior.R . prior_clusters.R . stick_breaking.R . table_update.R . true_cluster_labels.R . update_alpha.R . update_alpha_beta.R . update_concentration.R . update_g0.R . update_states.R . utilities.R . weibull_uniform_gamma.R .  Full dirichletprocess package functions and examples
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