{
  "_id": "6a1f3519b401979e73428598",
  "Package": "PICBayes",
  "Title": "Bayesian Models for Partly Interval-Censored Data",
  "Version": "1.0",
  "Date": "2021-08-04",
  "Author": "Chun Pan",
  "Maintainer": "Chun Pan <chunpan2003@hotmail.com>",
  "Description": "Contains functions to fit proportional hazards (PH) model\nto partly interval-censored (PIC) data (Pan et al. (2020)\n<doi:10.1177/0962280220921552>), PH model with spatial frailty\nto spatially dependent PIC data (Pan and Cai (2021)\n<doi:10.1080/03610918.2020.1839497>), and mixed effects PH\nmodel to clustered PIC data. Each random intercept/random\neffect can follow both a normal prior and a Dirichlet process\nmixture prior. It also includes the corresponding functions for\ngeneral interval-censored data.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-15 06:40:58 UTC",
    "User": "root"
  },
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2021-08-05 06:50:17 UTC",
  "RemoteUrl": "https://github.com/cran/PICBayes",
  "RemoteRef": "HEAD",
  "RemoteSha": "79becb9f75bc09e8d9a466638aa348e9602611b7",
  "MD5sum": "43f77c28ec5e1f33d5269bf92e1c524e",
  "_user": "cran",
  "_type": "src",
  "_file": "PICBayes_1.0.tar.gz",
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  "_created": "2026-05-15T06:40:58.000Z",
  "_published": "2026-06-02T19:55:05.171Z",
  "_distro": "noble",
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  "_buildurl": "https://github.com/r-universe/cran/actions/runs/25904253160",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/PICBayes",
  "_commit": {
    "id": "79becb9f75bc09e8d9a466638aa348e9602611b7",
    "author": "Chun Pan <chunpan2003@hotmail.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 1.0\n",
    "time": 1628146217
  },
  "_maintainer": {
    "name": "Chun Pan",
    "email": "chunpan2003@hotmail.com"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.5.0",
      "role": "Depends"
    },
    {
      "package": "coda",
      "role": "Depends"
    },
    {
      "package": "MCMCpack",
      "role": "Depends"
    },
    {
      "package": "survival",
      "role": "Depends"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 0,
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 188,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/PICBayes"
  },
  "_searchresults": 4,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/PICBayes.html",
    "manual.pdf"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
    {
      "version": "1.0",
      "date": "2021-08-05"
    }
  ],
  "_exports": [
    "clusterIC_int",
    "clusterIC_int_DP",
    "clusterIC_trt",
    "clusterIC_trt_DP",
    "clusterIC_Z",
    "clusterIC_Z_DP",
    "clusterPIC_int",
    "clusterPIC_int_DP",
    "clusterPIC_trt",
    "clusterPIC_trt_DP",
    "clusterPIC_Z",
    "clusterPIC_Z_DP",
    "coef.PICBayes",
    "IC",
    "logLik.PICBayes",
    "PIC",
    "PICBayes",
    "PICBayes.default",
    "PICBayes.formula",
    "plot.PICBayes",
    "spatialIC",
    "spatialPIC",
    "summary.PICBayes",
    "SurvtoLR"
  ],
  "_datasets": [
    {
      "name": "C",
      "title": "Adjacency matrix of 46 South Carolina counties",
      "object": "C",
      "file": "C.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": {},
      "rows": 46,
      "table": true,
      "tojson": true
    },
    {
      "name": "da1",
      "title": "Partly interva-censored data",
      "object": "da1",
      "file": "da1.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "L",
        "R",
        "y",
        "x1",
        "x2",
        "IC",
        "ID"
      ],
      "rows": 460,
      "table": true,
      "tojson": true
    },
    {
      "name": "da2",
      "title": "Clustered partly interva-censored data",
      "object": "da2",
      "file": "da2.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "L",
        "R",
        "y",
        "x1",
        "x2",
        "area",
        "IC",
        "ID"
      ],
      "rows": 920,
      "table": true,
      "tojson": true
    },
    {
      "name": "da3",
      "title": "Clustered partly interva-censored data",
      "object": "da3",
      "file": "da3.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "L",
        "R",
        "y",
        "x1",
        "x2",
        "area",
        "IC",
        "ID"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "da4",
      "title": "Clustered partly interva-censored data",
      "object": "da4",
      "file": "da4.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "L",
        "R",
        "y",
        "x1",
        "x2",
        "area",
        "IC",
        "ID"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "mCRC",
      "title": "Colorectal cancer data",
      "object": "mCRC",
      "file": "mCRC.rda",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "L",
        "R",
        "y",
        "TRT_C",
        "KRAS_C",
        "SITE",
        "IC",
        "ID"
      ],
      "rows": 855,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "PICBayes-package",
      "title": "Bayesian Models for Partly Interval-Censored Data and General Interval-Censored Data",
      "topics": [
        "PICBayes-package"
      ]
    },
    {
      "page": "C",
      "title": "Adjacency matrix of 46 South Carolina counties",
      "topics": [
        "C"
      ]
    },
    {
      "page": "clusterIC_int",
      "title": "PH model with random intercept for clustered general interval-censored data",
      "topics": [
        "clusterIC_int"
      ]
    },
    {
      "page": "clusterIC_int_DP",
      "title": "PH model with random intercept for clustered general interval-censored data",
      "topics": [
        "clusterIC_int_DP"
      ]
    },
    {
      "page": "clusterIC_trt",
      "title": "PH model with random intercept and random treatment for clustered general interval-censored data",
      "topics": [
        "clusterIC_trt"
      ]
    },
    {
      "page": "clusterIC_trt_DP",
      "title": "PH model with random intercept and random treatment for clustered general interval-censored data",
      "topics": [
        "clusterIC_trt_DP"
      ]
    },
    {
      "page": "clusterIC_Z",
      "title": "Mixed effects PH model for clustered general interval-censored data",
      "topics": [
        "clusterIC_Z"
      ]
    },
    {
      "page": "clusterIC_Z_DP",
      "title": "Mixed effects PH model for clustered general interval-censored data",
      "topics": [
        "clusterIC_Z_DP"
      ]
    },
    {
      "page": "clusterPIC_int",
      "title": "PH model with random intercept for clustered partly interval-censored data",
      "topics": [
        "clusterPIC_int"
      ]
    },
    {
      "page": "clusterPIC_int_DP",
      "title": "PH model with random intercept for clustered partly interval-censored data data",
      "topics": [
        "clusterPIC_int_DP"
      ]
    },
    {
      "page": "clusterPIC_trt",
      "title": "PH model with random intercept and random treatment for clustered partly interval-censored data",
      "topics": [
        "clusterPIC_trt"
      ]
    },
    {
      "page": "clusterPIC_trt_DP",
      "title": "PH model with random intercept and random treatment for clustered partly interval-censored data",
      "topics": [
        "clusterPIC_trt_DP"
      ]
    },
    {
      "page": "clusterPIC_Z",
      "title": "Mixed effects PH model for clustered partly interval-censored data",
      "topics": [
        "clusterPIC_Z"
      ]
    },
    {
      "page": "clusterPIC_Z_DP",
      "title": "Mixed effects PH model for clustered partly interval-censored data",
      "topics": [
        "clusterPIC_Z_DP"
      ]
    },
    {
      "page": "coef.PICBayes",
      "title": "Coef method for a PICBayes model",
      "topics": [
        "coef.PICBayes"
      ]
    },
    {
      "page": "da1",
      "title": "Partly interva-censored data",
      "topics": [
        "da1"
      ]
    },
    {
      "page": "da2",
      "title": "Clustered partly interva-censored data",
      "topics": [
        "da2"
      ]
    },
    {
      "page": "da3",
      "title": "Clustered partly interva-censored data",
      "topics": [
        "da3"
      ]
    },
    {
      "page": "da4",
      "title": "Clustered partly interva-censored data",
      "topics": [
        "da4"
      ]
    },
    {
      "page": "IC",
      "title": "PH model for general interval-censored data",
      "topics": [
        "IC"
      ]
    },
    {
      "page": "logLik.PICBayes",
      "title": "LogLik method for a PICBayes model",
      "topics": [
        "logLik.PICBayes"
      ]
    },
    {
      "page": "mCRC",
      "title": "Colorectal cancer data",
      "topics": [
        "mCRC"
      ]
    },
    {
      "page": "PIC",
      "title": "PH model for partly interval-censored data",
      "topics": [
        "PIC"
      ]
    },
    {
      "page": "PICBayes",
      "title": "Bayesian models for partly interval-censored data and general interval-censored data",
      "topics": [
        "PICBayes",
        "PICBayes.default",
        "PICBayes.formula"
      ]
    },
    {
      "page": "plot.PICBayes",
      "title": "Plot method for a PICBayes model",
      "topics": [
        "plot.PICBayes"
      ]
    },
    {
      "page": "spatialIC",
      "title": "PH model for spatial general interval-censored data",
      "topics": [
        "spatialIC"
      ]
    },
    {
      "page": "spatialPIC",
      "title": "PH model for spatial partly interval-censored data",
      "topics": [
        "spatialPIC"
      ]
    },
    {
      "page": "summary.PICBayes",
      "title": "Summary method for a PICBayes model",
      "topics": [
        "summary.PICBayes"
      ]
    },
    {
      "page": "SurvtoLR",
      "title": "Transform Surv object to data matrix with L and R columns",
      "topics": [
        "SurvtoLR"
      ]
    }
  ],
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    "lattice",
    "MASS",
    "Matrix",
    "MatrixModels",
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    "MCMCpack",
    "quantreg",
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  "_score": 1,
  "_indexed": true,
  "_nocasepkg": "picbayes",
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}