{ "_id": "6acb5d6bfe5cc25786e8ec97", "Package": "dirichletprocess", "Type": "Package", "Title": "Build Dirichlet Process Objects for Bayesian Modelling", "Version": "0.4.2.9000", "Authors@R": "c(\nperson(\"Gordon\", \"J. Ross\", email=\"gordon@gordonjross.co.uk\", role=c(\"aut\")),\nperson(\"Dean\", \"Markwick\", email=\"dean.markwick@talk21.com\", role=c(\"aut\", \"cre\")),\nperson(\"Kees\", \"Mulder\", email=\"keestimmulder@gmail.com\", role=c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-5387-3812\")),\nperson(\"Giovanni\", \"Sighinolfi\", email =\"giovanni.sighinolfi2@studio.unibo.it\", role=c(\"ctb\")),\nperson(\"Filippo Fiocchi\", email=\"filippofiocchi1@gmail.com\", role=c(\"ctb\"))\n)", "Maintainer": "Dean Markwick ", "Description": "Perform nonparametric Bayesian analysis using Dirichlet\nprocesses without the need to program the inference algorithms.\nUtilise included pre-built models or specify custom models and\nallow the 'dirichletprocess' package to handle the Markov chain\nMonte Carlo sampling. Our Dirichlet process objects can act as\nbuilding blocks for a variety of statistical models including\nand not limited to: density estimation, clustering and prior\ndistributions in hierarchical models. See Teh, Y. W. (2011)\n,\namong many other sources.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "URL": "https://github.com/dm13450/dirichletprocess,\nhttps://dm13450.github.io/dirichletprocess/", "BugReports": "https://github.com/dm13450/dirichletprocess/issues", "Config/roxygen2/version": "8.0.0", "Repository": "https://dm13450.r-universe.dev", "Date/Publication": "2026-08-12 04:00:49 UTC", "RemoteUrl": "https://github.com/dm13450/dirichletprocess", "RemoteRef": "HEAD", "RemoteSha": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-11 09:32:41 UTC", "User": "root" }, "Author": "Gordon J. Ross [aut],\nDean Markwick [aut, cre],\nKees Mulder [ctb] (ORCID: ),\nGiovanni Sighinolfi [ctb],\nFilippo Fiocchi [ctb]", "_user": "dm13450", "_type": "src", "_file": "dirichletprocess_0.4.2.9000.tar.gz", "_fileid": "https://r2.ropensci.org/685151cec99c06dd3e67f05cf0046c16160a6c4ba65bbbf2d8239ec4e3226eb1", "_filesize": 1542505, "_sha256": "685151cec99c06dd3e67f05cf0046c16160a6c4ba65bbbf2d8239ec4e3226eb1", "_expires": "2027-01-19T09:56:58.000Z", "_created": "2026-10-11T09:32:41.000Z", "_published": "2026-10-11T09:56:59.782Z", "_buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673", "_status": "success", "_host": "GitHub-Actions", "_jobs": [ { "job": 114438554193, "time": 148, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11698770443" }, { "job": 114438554239, "time": 147, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11699000673" }, { "job": 114438554259, "time": 237, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11698568514" }, { "job": 114438554235, "time": 150, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11698911802" }, { "job": 114437939644, "time": 203, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11698720886" }, { "job": 114438554202, "time": 92, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11699125291" }, { "job": 114438554217, "time": 121, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11698255928" }, { "job": 114438554256, "time": 159, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11698296620" }, { "job": 114438554270, "time": 103, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11698521389" } ], "_upstream": "https://github.com/dm13450/dirichletprocess", "_commit": { "id": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "author": "Dean ", "committer": "GitHub ", "message": "Merge pull request #33 from dm13450/housekeeping\n\nHousekeeping", "time": 1786507249 }, "_maintainer": { "name": "Dean Markwick", "email": "dean.markwick@talk21.com", "login": "dm13450", "twitter": "@DeanMarkwick", "description": "Quant", "uuid": 8281054 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.10", "role": "Depends" }, { "package": "gtools", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "mvtnorm", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "tidyr", "role": "Suggests" }, { "package": "dplyr", "role": "Suggests" } ], "_owner": "dm13450", "_selfowned": true, "_usedby": 2, "_updates": [ { "week": "2026-33", "n": 1 } ], "_tags": [], "_topics": [ "bayesian", "bayesian-inference", "bayesian-statistics", "dirichlet-process", "mcmc" ], "_stars": 62, "_contributors": [ { "user": "dm13450", "count": 136, "uuid": 8281054 }, { "user": "keesmulder", "count": 53, "uuid": 7806295 }, { "user": "filippofiocchi", "count": 3, "uuid": 52209617 } ], "_userbio": { "uuid": 8281054, "type": "user", "name": "Dean", "followers": 144, "description": "Quant" }, "_downloads": { "count": 1572, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/dirichletprocess" }, "_devurl": "https://github.com/dm13450/dirichletprocess", "_pkgdown": "https://dm13450.github.io/dirichletprocess/", "_searchresults": 99, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/dirichletprocess.html", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md" ], "_homeurl": "https://github.com/dm13450/dirichletprocess", "_realowner": "dm13450", "_cranurl": true, "_releases": [ { "version": "0.2.0", "date": "2018-01-29" }, { "version": "0.2.1", "date": "2018-04-18" }, { "version": "0.2.2", "date": "2018-11-23" }, { "version": "0.3.0", "date": "2019-05-03" }, { "version": "0.3.1", "date": "2019-12-11" }, { "version": "0.3.1.1", "date": "2020-04-03" }, { "version": "0.4.0", "date": "2020-06-13" }, { "version": "0.4.1", "date": "2023-03-10" }, { "version": "0.4.2", "date": "2023-08-25" } ], "_exports": [ "AlphaPriorPosteriorPlot", "AlphaTraceplot", "BetaMixture2Create", "BetaMixtureCreate", "Burn", "ChangeObservations", "ClusterComponentUpdate", "ClusterLabelPredict", "ClusterParameterUpdate", "ClusterTraceplot", "DiagnosticPlots", "DirichletHMMCreate", "DirichletProcessBeta", "DirichletProcessBeta2", "DirichletProcessCreate", "DirichletProcessExponential", "DirichletProcessGaussian", "DirichletProcessGaussianFixedVariance", "DirichletProcessHierarchicalBeta", "DirichletProcessHierarchicalMvnormal2", "DirichletProcessMvnormal", "DirichletProcessMvnormal2", "DirichletProcessWeibull", "ExponentialMixtureCreate", "Fit", "GaussianFixedVarianceMixtureCreate", "GaussianMixtureCreate", "GlobalParameterUpdate", "HierarchicalBetaCreate", "HierarchicalMvnormal2Create", "Initialise", "Likelihood", "LikelihoodDP", "LikelihoodFunction", "LikelihoodTraceplot", "MixingDistribution", "Mvnormal2Create", "MvnormalCreate", "PenalisedLikelihood", "piDirichlet", "plot_dirichletprocess_multivariate", "plot_dirichletprocess_univariate", "PosteriorClusters", "PosteriorDraw", "PosteriorFrame", "PosteriorFunction", "PosteriorParameters", "Predictive", "PriorClusters", "PriorDensity", "PriorDraw", "PriorParametersUpdate", "StickBreaking", "true_cluster_labels", "UpdateAlpha", "UpdateAlphaBeta", "WeibullMixtureCreate", "weighted_function_generator" ], "_datasets": [ { "name": "rats", "title": "Tumour incidences in rats", "object": "rats", "class": [ "data.frame" ], "fields": [ "y", "N" ], "rows": 71, "table": true, "tojson": true } ], "_help": [ { "page": "BetaMixture2Create", "title": "Create a Beta mixture with zeros at the boundaries.", "topics": [ "BetaMixture2Create" ] }, { "page": "BetaMixtureCreate", "title": "Create a Beta mixing distribution.", "topics": [ "BetaMixtureCreate" ] }, { "page": "Burn", "title": "Add burn-in to a dirichletprocess object", "topics": [ "Burn" ] }, { "page": "ChangeObservations", "title": "Change the observations of fitted Dirichlet Process.", "topics": [ "ChangeObservations" ] }, { "page": "ClusterComponentUpdate", "title": "Update the component of the Dirichlet process", "topics": [ "ClusterComponentUpdate", "ClusterComponentUpdate.conjugate", "ClusterComponentUpdate.hierarchical" ] }, { "page": "ClusterLabelPredict", "title": "Predict the cluster labels of some new data.", "topics": [ "ClusterLabelPredict" ] }, { "page": "ClusterParameterUpdate", "title": "Update the cluster parameters of the Dirichlet process.", "topics": [ "ClusterParameterUpdate" ] }, { "page": "DiagnosticPlots", "title": "Diagnostic plots for dirichletprocess objects", "topics": [ "AlphaPriorPosteriorPlot", "AlphaTraceplot", "ClusterTraceplot", "DiagnosticPlots", "LikelihoodTraceplot" ] }, { "page": "DirichletHMMCreate", "title": "Create a generic Dirichlet process hidden Markov Model", "topics": [ "DirichletHMMCreate" ] }, { "page": "dirichletprocess", "title": "A flexible package for fitting Bayesian non-parametric models.", "topics": [ "dirichletprocess" ] }, { "page": "DirichletProcessBeta", "title": "Dirichlet process mixture of the Beta distribution.", "topics": [ "DirichletProcessBeta" ] }, { "page": "DirichletProcessBeta2", "title": "Dirichlet process mixture of Beta distributions with a Uniform Pareto base measure.", "topics": [ "DirichletProcessBeta2" ] }, { "page": "DirichletProcessCreate", "title": "Create a Dirichlet Process object", "topics": [ "DirichletProcessCreate" ] }, { "page": "DirichletProcessExponential", "title": "Create a Dirichlet Mixture of Exponentials", "topics": [ "DirichletProcessExponential" ] }, { "page": "DirichletProcessGaussian", "title": "Create a Dirichlet Mixture of Gaussians", "topics": [ "DirichletProcessGaussian" ] }, { "page": "DirichletProcessGaussianFixedVariance", "title": "Create a Dirichlet Mixture of the Gaussian Distribution with fixed variance.", "topics": [ "DirichletProcessGaussianFixedVariance" ] }, { "page": "DirichletProcessHierarchicalBeta", "title": "Create a Hierarchical Dirichlet Mixture of Beta Distributions", "topics": [ "DirichletProcessHierarchicalBeta" ] }, { "page": "DirichletProcessHierarchicalMvnormal2", "title": "Create a Hierarchical Dirichlet Mixture of semi-conjugate Multivariate Normal Distributions", "topics": [ "DirichletProcessHierarchicalMvnormal2" ] }, { "page": "DirichletProcessMvnormal", "title": "Create a Dirichlet mixture of multivariate normal distributions.", "topics": [ "DirichletProcessMvnormal" ] }, { "page": "DirichletProcessMvnormal2", "title": "Create a Dirichlet mixture of multivariate normal distributions with semi-conjugate prior.", "topics": [ "DirichletProcessMvnormal2" ] }, { "page": "DirichletProcessWeibull", "title": "Create a Dirichlet Mixture of the Weibull distribution", "topics": [ "DirichletProcessWeibull" ] }, { "page": "ExponentialMixtureCreate", "title": "Create a Exponential mixing distribution", "topics": [ "ExponentialMixtureCreate" ] }, { "page": "Fit", "title": "Fit the Dirichlet process object", "topics": [ "Fit" ] }, { "page": "Fit.markov", "title": "Fit a Hidden Markov Dirichlet Process Model", "topics": [ "Fit.markov" ] }, { "page": "GaussianFixedVarianceMixtureCreate", "title": "Create a Gaussian Mixing Distribution with fixed variance.", "topics": [ "GaussianFixedVarianceMixtureCreate" ] }, { "page": "GaussianMixtureCreate", "title": "Create a Normal mixing distribution", "topics": [ "GaussianMixtureCreate" ] }, { "page": "GlobalParameterUpdate", "title": "Update the parameters of the hierarchical Dirichlet process object.", "topics": [ "GlobalParameterUpdate" ] }, { "page": "HierarchicalBetaCreate", "title": "Create a Mixing Object for a hierarchical Beta Dirichlet process object.", "topics": [ "HierarchicalBetaCreate" ] }, { "page": "HierarchicalMvnormal2Create", "title": "Create a Mixing Object for a hierarchical semi-conjugate Multivariate Normal Dirichlet process object.", "topics": [ "HierarchicalMvnormal2Create" ] }, { "page": "Initialise", "title": "Initialise a Dirichlet process object", "topics": [ "Initialise" ] }, { "page": "Likelihood", "title": "Mixing Distribution Likelihood", "topics": [ "Likelihood", "Likelihood.beta", "Likelihood.beta2", "Likelihood.exponential", "Likelihood.mvnormal", "Likelihood.mvnormal2", "Likelihood.normal", "Likelihood.normalFixedVariance" ] }, { "page": "LikelihoodDP", "title": "The likelihood of the Dirichlet process object", "topics": [ "LikelihoodDP" ] }, { "page": "LikelihoodFunction", "title": "The Likelihood function of a Dirichlet process object.", "topics": [ "LikelihoodFunction" ] }, { "page": "MixingDistribution", "title": "Create a mixing distribution object", "topics": [ "MixingDistribution" ] }, { "page": "Mvnormal2Create", "title": "Create a multivariate normal mixing distribution with semi conjugate prior", "topics": [ "Mvnormal2Create" ] }, { "page": "MvnormalCreate", "title": "Create a multivariate normal mixing distribution", "topics": [ "MvnormalCreate" ] }, { "page": "PenalisedLikelihood", "title": "Calculate the parameters that maximise the penalised likelihood.", "topics": [ "PenalisedLikelihood", "PenalisedLikelihood.beta", "PenalisedLikelihood.default" ] }, { "page": "plot.dirichletprocess", "title": "Plot the Dirichlet process object", "topics": [ "plot.dirichletprocess", "plot_dirichletprocess_multivariate", "plot_dirichletprocess_univariate" ] }, { "page": "PosteriorClusters", "title": "Generate the posterior clusters of a Dirichlet Process", "topics": [ "PosteriorClusters" ] }, { "page": "PosteriorDraw", "title": "Draw from the posterior distribution", "topics": [ "PosteriorDraw", "PosteriorDraw.exponential", "PosteriorDraw.mvnormal", "PosteriorDraw.mvnormal2", "PosteriorDraw.normal", "PosteriorDraw.normalFixedVariance", "PosteriorDraw.weibull" ] }, { "page": "PosteriorFrame", "title": "Calculate the posterior mean and quantiles from a Dirichlet process object.", "topics": [ "PosteriorFrame" ] }, { "page": "PosteriorFunction", "title": "Generate the posterior function of the Dirichlet function", "topics": [ "PosteriorFunction" ] }, { "page": "PosteriorParameters", "title": "Calculate the posterior parameters for a conjugate prior.", "topics": [ "PosteriorParameters", "PosteriorParameters.mvnormal", "PosteriorParameters.normal", "PosteriorParameters.normalFixedVariance" ] }, { "page": "Predictive", "title": "Calculate how well the prior predicts the data.", "topics": [ "Predictive", "Predictive.exponential", "Predictive.mvnormal", "Predictive.normal", "Predictive.normalFixedVariance" ] }, { "page": "print.dirichletprocess", "title": "Print the Dirichlet process object", "topics": [ "print.dirichletprocess" ] }, { "page": "PriorClusters", "title": "Draw prior clusters and weights from the Dirichlet process", "topics": [ "PriorClusters" ] }, { "page": "PriorDensity", "title": "Calculate the prior density of a mixing distribution", "topics": [ "PriorDensity", "PriorDensity.beta", "PriorDensity.beta2", "PriorDensity.weibull" ] }, { "page": "PriorDraw", "title": "Draw from the prior distribution", "topics": [ "PriorDraw", "PriorDraw.beta", "PriorDraw.beta2", "PriorDraw.exponential", "PriorDraw.mvnormal", "PriorDraw.mvnormal2", "PriorDraw.normal", "PriorDraw.normalFixedVariance", "PriorDraw.weibull" ] }, { "page": "PriorFunction", "title": "Generate the prior function of the Dirichlet process", "topics": [ "PriorFunction" ] }, { "page": "PriorParametersUpdate", "title": "Update the prior parameters of a mixing distribution", "topics": [ "PriorParametersUpdate", "PriorParametersUpdate.beta", "PriorParametersUpdate.weibull" ] }, { "page": "rats", "title": "Tumour incidences in rats", "topics": [ "rats" ] }, { "page": "StickBreaking", "title": "The Stick Breaking representation of the Dirichlet process.", "topics": [ "piDirichlet", "StickBreaking" ] }, { "page": "true_cluster_labels", "title": "Identifies the correct clusters labels, in any dimension, when cluster parameters and global parameters are matched.", "topics": [ "true_cluster_labels" ] }, { "page": "UpdateAlpha", "title": "Update the Dirichlet process concentration parameter.", "topics": [ "UpdateAlpha", "UpdateAlpha.default", "UpdateAlpha.hierarchical" ] }, { "page": "UpdateAlphaBeta", "title": "Update the alpha and beta parameter of a hidden Markov Dirichlet process model.", "topics": [ "UpdateAlphaBeta" ] }, { "page": "WeibullMixtureCreate", "title": "Create a Weibull mixing distribution.", "topics": [ "WeibullMixtureCreate" ] }, { "page": "weighted_function_generator", "title": "Generate a weighted function.", "topics": [ "weighted_function_generator" ] } ], "_readme": "https://github.com/dm13450/dirichletprocess/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "farver", "ggplot2", "glue", "gtable", "gtools", "isoband", "labeling", "lifecycle", "mvtnorm", "R6", "RColorBrewer", "rlang", "S7", "scales", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "dirichletprocess.Rnw", "filename": "dirichletprocess.pdf", "title": "dirichletprocess: An R Package for Fitting Complex Bayesian Nonparametric Models", "engine": "utils::Sweave", "headings": [ "Introduction", "Background information", "Package Overview", "Advanced Features" ], "created": "2017-12-08 14:23:39", "modified": "2020-10-14 18:51:15", "commits": 14 } ], "_score": 7.762630676182836, "_indexed": true, "_nocasepkg": "dirichletprocess", "_universes": [ "dm13450" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.4.2.9000", "date": "2026-10-11T09:34:43.000Z", "distro": "resolute", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/0da2982942918707990e7ebc6fe000f02399d2257b52b6c3249dba0659af0145", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.6.1", "os": "linux", "version": "0.4.2.9000", "date": "2026-10-11T09:34:43.000Z", "distro": "resolute", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/57428cad3212dd66d8c5a090d7bebbddc68cc036bba89bb8e86c0722cbd6222c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.5.3", "os": "mac", "version": "0.4.2.9000", "date": "2026-10-11T09:55:17.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/ac688fcf475e46b1b6b28e5592742662635afa8ab15ad1630f5f8fa8ff1971ab", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.6.1", "os": "mac", "version": "0.4.2.9000", "date": "2026-10-11T09:53:55.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/513d805132d502144499987931adf443ec8ac98cd5b0a59fa4e64464f7d908e3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.6.0", "os": "wasm", "version": "0.4.2.9000", "date": "2026-10-11T09:34:36.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/e38b9d69955720bf2df4c72b8a6b940be2dea584ac9b5cb07bd9608f21a33dd0", "status": "success", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.7.0", "os": "win", "version": "0.4.2.9000", "date": "2026-10-11T09:34:14.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/c0afd18647a57f844cbc30b9dc7824943135a9e56498152373261736b78f964f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.5.3", "os": "win", "version": "0.4.2.9000", "date": "2026-10-11T09:34:43.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/7d458a0d6b6d3fa300b856f359f9497c9ab59642232ead2feb60b76e7eb4ec10", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" }, { "r": "4.6.1", "os": "win", "version": "0.4.2.9000", "date": "2026-10-11T09:34:09.000Z", "commit": "6b0b15bb7a30423f726df265f4f344c2ab09a857", "fileid": "https://r2.ropensci.org/8e2c756a51ddd74d56e7b918bd949da14c2307260381d00929349d9790a66cde", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/dm13450/actions/runs/38128540673" } ] }