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dirichletprocess
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]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.dirichletprocess . https://github.com/dm13450/dirichletprocess/issues . https://github.com/dm13450/dirichletprocess . https://dm13450.github.io/dirichletprocess/ . dirichletprocess results . dirichletprocess.pdf . dirichletprocess: An R Package for Fitting Complex Bayesian Nonparametric Models . dirichletprocess_0.4.2.tar.gz . dirichletprocess_0.4.2.zip . dirichletprocess_0.4.2.zip . dirichletprocess_0.4.2.zip . dirichletprocess_0.4.2.tgz . dirichletprocess_0.4.2.tgz . dirichletprocess_0.4.2.tgz . dirichletprocess_0.4.2.tgz . dirichletprocess archive . https://CRAN.R-project.org/package=dirichletprocess .
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 10 May. 2025.
Previous versions and publish date:
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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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