{
  "_id": "6ac63b47f511ae58c09a84bc",
  "Package": "telescope",
  "Version": "0.2-2",
  "Encoding": "UTF-8",
  "Title": "Bayesian Mixtures with an Unknown Number of Components",
  "Authors@R": "c(person(\"Gertraud\", \"Malsiner-Walli\", role = c(\"aut\", \"cre\"),\nemail = \"Gertraud.Malsiner-Walli@wu.ac.at\",\ncomment = c(ORCID = \"0000-0002-1213-4749\")),\nperson(\"Bettina\", \"Grün\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-7265-4773\")),\nperson(\"Sylvia\", \"Frühwirth-Schnatter\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-0516-5552\")))",
  "Description": "Fits Bayesian finite mixtures with an unknown number of\ncomponents using the telescoping sampler and different\ncomponent distributions. For more details see\nFrühwirth-Schnatter et al. (2021) <doi:10.1214/21-BA1294>,\nMalsiner-Walli et al. (in press)\n<doi:10.1007/s11634-025-00640-x> and Malsiner-Walli et al.\n(2026) <doi:10.48550/arXiv.2603.00277>.",
  "VignetteBuilder": "knitr, rmarkdown",
  "License": "GPL-2",
  "RoxygenNote": "7.3.3",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-10-07 09:55:15 UTC",
    "User": "root"
  },
  "Author": "Gertraud Malsiner-Walli [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-1213-4749>), Bettina Grün [aut]\n(ORCID: <https://orcid.org/0000-0001-7265-4773>), Sylvia\nFrühwirth-Schnatter [aut] (ORCID:\n<https://orcid.org/0000-0003-0516-5552>)",
  "Maintainer": "Gertraud Malsiner-Walli <Gertraud.Malsiner-Walli@wu.ac.at>",
  "Repository": "https://gertraudmalsinerwalli.r-universe.dev",
  "Date/Publication": "2026-04-10 11:15:55 UTC",
  "RemoteUrl": "https://github.com/cran/telescope",
  "RemoteRef": "HEAD",
  "RemoteSha": "c396a9ba41c71c4a665421006765d848ce88ab23",
  "_user": "gertraudmalsinerwalli",
  "_type": "src",
  "_file": "telescope_0.2-2.tar.gz",
  "_fileid": "https://r2.ropensci.org/bf859afd9e9cc88b4befbe3ccdd5966673e682b832ade6076d8166b78a971b42",
  "_filesize": 3584044,
  "_sha256": "bf859afd9e9cc88b4befbe3ccdd5966673e682b832ade6076d8166b78a971b42",
  "_expires": "2027-01-15T12:29:57.000Z",
  "_created": "2026-10-07T09:55:15.000Z",
  "_published": "2026-10-07T12:29:59.258Z",
  "_buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_jobs": [
    {
      "job": 112734723651,
      "time": 134,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "11473314873"
    },
    {
      "job": 112734723786,
      "time": 137,
      "config": "linux-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "11474570181"
    },
    {
      "job": 112734723638,
      "time": 159,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "11481149451"
    },
    {
      "job": 112734723728,
      "time": 167,
      "config": "macos-release-arm64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "11481698662"
    },
    {
      "job": 112732220353,
      "time": 349,
      "config": "source",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "11473997221"
    },
    {
      "job": 112734723680,
      "time": 108,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "11474002506"
    },
    {
      "job": 112734723707,
      "time": 99,
      "config": "windows-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "11474610003"
    },
    {
      "job": 112734723824,
      "time": 69,
      "config": "windows-oldrel-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "11474306016"
    },
    {
      "job": 112734723949,
      "time": 84,
      "config": "windows-release-x86_64",
      "r": "4.6.1",
      "check": "OK",
      "artifact": "11473668744"
    }
  ],
  "_upstream": "https://github.com/cran/telescope",
  "_commit": {
    "id": "c396a9ba41c71c4a665421006765d848ce88ab23",
    "author": "Gertraud Malsiner-Walli <Gertraud.Malsiner-Walli@wu.ac.at>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.2-2\n",
    "time": 1775819755
  },
  "_maintainer": {
    "name": "Gertraud Malsiner-Walli",
    "email": "gertraud.malsiner-walli@wu.ac.at",
    "login": "gertraudmalsinerwalli",
    "description": "",
    "uuid": 165141239,
    "orcid": "0000-0002-1213-4749"
  },
  "_distro": "resolute",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.0.0",
      "role": "Depends"
    },
    {
      "package": "abind",
      "role": "Imports"
    },
    {
      "package": "bayesm",
      "role": "Imports"
    },
    {
      "package": "DirichletReg",
      "role": "Imports"
    },
    {
      "package": "extraDistr",
      "role": "Imports"
    },
    {
      "package": "graphics",
      "role": "Imports"
    },
    {
      "package": "grDevices",
      "role": "Imports"
    },
    {
      "package": "MCMCpack",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "mvtnorm",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "invgamma",
      "role": "Suggests"
    },
    {
      "package": "klaR",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "mclust",
      "role": "Suggests"
    },
    {
      "package": "poLCA",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-15",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "0.2-2",
      "date": "2026-04-10"
    }
  ],
  "_stars": 0,
  "_contributors": [
    {
      "user": "gertraudmalsinerwalli",
      "count": 4,
      "uuid": 165141239
    }
  ],
  "_userbio": {
    "uuid": 165141239,
    "type": "user",
    "name": "GertraudMalsinerWalli",
    "followers": 0
  },
  "_downloads": {
    "count": 363,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/telescope"
  },
  "_searchresults": 4,
  "_rbuild": "4.6.1",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/manual.pdf",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/telescope.html"
  ],
  "_realowner": "gertraudmalsinerwalli",
  "_cranurl": false,
  "_releases": [
    {
      "version": "0.1-0",
      "date": "2024-06-15"
    },
    {
      "version": "0.2-0",
      "date": "2025-01-23"
    },
    {
      "version": "0.2-1",
      "date": "2025-08-18"
    },
    {
      "version": "0.2-2",
      "date": "2026-04-10"
    }
  ],
  "_exports": [
    "identifyLCAMixture",
    "identifyMixture",
    "plotBubble",
    "plotScatter",
    "priorOnAlpha_spec",
    "priorOnE0_spec",
    "priorOnK_spec",
    "sampleLCA",
    "sampleLCAMixture",
    "sampleMultNormMixture",
    "samplePoisMixture",
    "sampleUniNormMixture"
  ],
  "_datasets": [
    {
      "name": "SimData",
      "title": "Simulated Multivariate Binary Data",
      "object": "SimData",
      "file": "SimData.csv.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "y1",
        "y2",
        "y3",
        "y4",
        "y5",
        "y6",
        "y7",
        "y8",
        "y9",
        "y10",
        "y11",
        "y12",
        "y13",
        "y14",
        "y15",
        "y16",
        "y17",
        "y18",
        "y19",
        "y20",
        "y21",
        "y22",
        "y23",
        "y24",
        "y25",
        "y26",
        "y27",
        "y28",
        "y29",
        "y30",
        "z"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "identifyLCAMixture",
      "title": "Solve Label Switching and Identify a Mixture of LCA Models",
      "topics": [
        "identifyLCAMixture"
      ]
    },
    {
      "page": "identifyMixture",
      "title": "Solve Label Switching and Identify Mixture",
      "topics": [
        "identifyMixture"
      ]
    },
    {
      "page": "plotBubble",
      "title": "Plot Multivariate Categorical Data",
      "topics": [
        "plotBubble"
      ]
    },
    {
      "page": "plotScatter",
      "title": "Pairwise Scatter Plots of the Data",
      "topics": [
        "plotScatter"
      ]
    },
    {
      "page": "priorOnAlpha_spec",
      "title": "Specify Prior on alpha",
      "topics": [
        "priorOnAlpha_spec"
      ]
    },
    {
      "page": "priorOnE0_spec",
      "title": "Specify Prior on e0",
      "topics": [
        "priorOnE0_spec"
      ]
    },
    {
      "page": "priorOnK_spec",
      "title": "Specify Prior on K",
      "topics": [
        "priorOnK_spec"
      ]
    },
    {
      "page": "sampleLCA",
      "title": "Telescoping Sampling of an LCA Model with a Prior on the Number of Components K",
      "topics": [
        "sampleLCA"
      ]
    },
    {
      "page": "sampleLCAMixture",
      "title": "Telescoping Sampling of a Mixture of LCA Models with a Prior on the Number of Components K",
      "topics": [
        "sampleLCAMixture"
      ]
    },
    {
      "page": "sampleMultNormMixture",
      "title": "Telescoping Sampling of a Bayesian Finite Multivariate Gaussian Mixture with a Prior on the Number of Components K",
      "topics": [
        "sampleMultNormMixture"
      ]
    },
    {
      "page": "samplePoisMixture",
      "title": "Telescoping Sampling of a Bayesian Finite Poisson Mixture with a Prior on the Number of Components K",
      "topics": [
        "samplePoisMixture"
      ]
    },
    {
      "page": "sampleUniNormMixture",
      "title": "Telescoping Sampling of a Bayesian Finite Univariate Gaussian Mixture with a Prior on the Number of Components K",
      "topics": [
        "sampleUniNormMixture"
      ]
    },
    {
      "page": "SimData",
      "title": "Simulated Multivariate Binary Data",
      "topics": [
        "SimData"
      ]
    }
  ],
  "_rundeps": [
    "abind",
    "bayesm",
    "coda",
    "digest",
    "DirichletReg",
    "extraDistr",
    "Formula",
    "generics",
    "lattice",
    "MASS",
    "Matrix",
    "MatrixModels",
    "maxLik",
    "mcmc",
    "MCMCpack",
    "miscTools",
    "mvtnorm",
    "quantreg",
    "Rcpp",
    "RcppArmadillo",
    "sandwich",
    "SparseM",
    "survival",
    "zoo"
  ],
  "_vignettes": [
    {
      "source": "Bayesian_LCA.Rmd",
      "filename": "Bayesian_LCA.html",
      "title": "Bayesian Latent Class Analysis Models with the Telescoping Sampler",
      "author": "Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "The fear data set",
        "Model specification",
        "Specification of the MCMC simulation and prior parameters",
        "MCMC sampling",
        "Convergence diagnostics of the run",
        "Identification of the mixture model",
        "Step 1: Estimate $K_+$ and $K$",
        "Step 2: Extracting the draws with exactly $\\hat{K}_+$ non-empty components",
        "Step 3: Clustering and relabeling of the MCMC draws",
        "Step 4: Estimating data cluster specific parameters and determining the final partition",
        "References"
      ],
      "created": "2024-06-16 02:45:42",
      "modified": "2025-01-23 14:35:35",
      "commits": 2
    },
    {
      "source": "Bayesian_LCA_mixtures.Rmd",
      "filename": "Bayesian_LCA_mixtures.html",
      "title": "Bayesian Mixture of Latent Class Analysis Models with the Telescoping Sampler",
      "author": "Gertraud Malsiner-Walli, Bettina Grün, Sylvia Frühwirth-Schnatter",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Data",
        "Model specification",
        "Specification of the MCMC simulation and prior parameters",
        "MCMC sampling",
        "Convergence diagnostics of the run",
        "Identification of the mixture model",
        "Step 1: Estimate $K_+$ and $K$",
        "Step 2: Extracting the draws with exactly $\\hat{K}_+$ non-empty components",
        "Step 3: Clustering and relabeling of the MCMC draws",
        "Step 4: Estimating data cluster specific parameters and determining the final partition",
        "Step 4: Visualizing the posterior component occurrence and precision distributions mu_k and  phi_j.",
        "References"
      ],
      "created": "2025-01-23 14:35:35",
      "modified": "2026-04-10 11:15:55",
      "commits": 2
    },
    {
      "source": "Bayesian_mult_Gaussian_mixtures.Rmd",
      "filename": "Bayesian_mult_Gaussian_mixtures.html",
      "title": "Bayesian Multivariate Gaussian Mixtures with the Telescoping Sampler",
      "author": "Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "The thyroid data set",
        "Model specification",
        "Specification of the simulation and prior parameters",
        "MCMC sampling",
        "Convergence diagnostics of the run",
        "Identification of the mixture model",
        "Step 1: Estimating $K_+$ and $K$",
        "Step 2: Extracting the draws with exactly $\\hat{K}_+$ non-empty components",
        "Step 3: Clustering and relabeling of the MCMC draws in the point process representation",
        "Step 4: Estimating data cluster specific parameters and determining the final partition",
        "Step 5: Visualizing the estimated classification",
        "References"
      ],
      "created": "2024-06-16 02:45:42",
      "modified": "2025-01-23 14:35:35",
      "commits": 2
    },
    {
      "source": "Bayesian_Poisson_mixtures.Rmd",
      "filename": "Bayesian_Poisson_mixtures.html",
      "title": "Bayesian Poisson Mixtures with the Telescoping Sampler",
      "author": "Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "The eye data set",
        "Model specification",
        "Specification of the simulation and prior parameters",
        "MCMC sampling",
        "Convergence diagnostics of the run",
        "Identification of the mixture model",
        "Step 1: Estimate $K_+$ and $K$",
        "Step 2: Extract those draws which correspond to samples with exactly $\\hat{K}_+$ filled components",
        "Step 3: Clustering and relabeling of the MCMC draws, with $\\hat{K}_+$ being the estimated number of data clusters",
        "References"
      ],
      "created": "2024-06-16 02:45:42",
      "modified": "2025-01-23 14:35:35",
      "commits": 2
    },
    {
      "source": "Bayesian_univ_Gaussian_mixtures.Rmd",
      "filename": "Bayesian_univ_Gaussian_mixtures.html",
      "title": "Bayesian Univariate Gaussian Mixtures with the Telescoping Sampler",
      "author": "Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "The Galaxy data set",
        "Model specification",
        "Specification of the MCMC simulation and prior parameters",
        "MCMC sampling",
        "Convergence diagnostics of the run",
        "Identification of the mixture model",
        "Step 1: Estimating $K_+$ and $K$",
        "Step 2: Extracting the draws with exactly $\\hat{K}_+$ non-empty components",
        "Step 3: Clustering and relabeling of the MCMC draws in the point process representation",
        "Step 4: Estimating data cluster specific parameters and determing the final partition",
        "Step 5: Visualizing the estimated classification",
        "References"
      ],
      "created": "2024-06-16 02:45:42",
      "modified": "2025-01-23 14:35:35",
      "commits": 2
    },
    {
      "source": "CliPS_diabetes.Rmd",
      "filename": "CliPS_diabetes.html",
      "title": "Using CliPS to Identify a Dynamic Mixture of Finite Mixtures of Multivariate Gaussian Distributions -- Case Study: Diabetes Data",
      "author": "Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Step 1: Define a mixture model",
        "Step 2:  MCMC sampling from the posterior",
        "Step 2b: Post-processing the MCMC draws",
        "Steps 3-4-5: Clustering of the draws",
        "Step 6: Characterization of the cluster distributions",
        "References"
      ],
      "created": "2026-04-10 11:15:55",
      "modified": "2026-04-10 11:15:55",
      "commits": 1
    }
  ],
  "_score": 2.778151250383644,
  "_indexed": true,
  "_nocasepkg": "telescope",
  "_universes": [
    "gertraudmalsinerwalli"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.2-2",
      "date": "2026-10-07T09:57:40.000Z",
      "distro": "resolute",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/498aeaabfa4c0e098b0fec2ddb8e20398fd93086bd473184a76964fdc250b3fb",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.6.1",
      "os": "linux",
      "version": "0.2-2",
      "date": "2026-10-07T09:57:41.000Z",
      "distro": "resolute",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/929f408d26d4d45db767354186a4265d1054d4cc8622ec3241ee643acbf76493",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.2-2",
      "date": "2026-10-07T12:28:44.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/85248f2cbef3cb84b1cae85ecc342dba68199eea6af71db2466fc2e0254bd52d",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.6.1",
      "os": "mac",
      "version": "0.2-2",
      "date": "2026-10-07T12:27:16.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/71e3fae364e273857a3e1ff51a42060bd79df882d89641d4103a1c7a6334f86f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.2-2",
      "date": "2026-10-07T09:57:29.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/1b00f0166a20ffc91d6d9737f604c8e44c3317c2eef5bf69c80b971e2be340fc",
      "status": "success",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.2-2",
      "date": "2026-10-07T09:56:54.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/e4df015752a21756d46c80f193252f06a6eb39e1900e9f193ecb1c0cea46a5d4",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "0.2-2",
      "date": "2026-10-07T09:56:36.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/677192547727300c0d43e48f1b585920194c2ec57f9ca2f5ec83fc9b6002ef2e",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    },
    {
      "r": "4.6.1",
      "os": "win",
      "version": "0.2-2",
      "date": "2026-10-07T09:56:38.000Z",
      "commit": "c396a9ba41c71c4a665421006765d848ce88ab23",
      "fileid": "https://r2.ropensci.org/d8224076cef2dfcdee101b3d8f0ced7225e9f0b48ff442e758ac7ffa6d57e37f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/gertraudmalsinerwalli/actions/runs/37602866543"
    }
  ]
}