{
  "_id": "6a346e0a3efcd9bda43c4f7b",
  "Package": "wnpmle",
  "Title": "Weighted NPMLE for Recurrent Events with a Competing Terminal\nEvent",
  "Version": "0.1.2",
  "Authors@R": "person(\"Anna\", \"Bellach\",\nemail = \"abellach.biostat@gmail.com\",\nrole = c(\"aut\", \"cre\"))",
  "Description": "Provides regression modeling and prediction for the\nmarginal mean of recurrent events in the presence of a\ncompeting terminal event using the weighted nonparametric\nmaximum likelihood estimator (wNPMLE) of Bellach and Kosorok\n(2026) <doi:10.48550/arXiv.2605.25934>. Two classes of\ntransformation models are implemented: Box-Cox transformation\nmodels and logarithmic transformation models. These extend the\nproportional means model of Ghosh and Lin (2002)\n<doi:10.17615/pt0g-y207> and the transformation model framework\nof Zeng and Lin (2006) <doi:10.1093/biomet/93.3.627>. Parameter\nestimation is performed using automatic differentiation through\nthe Template Model Builder (TMB) framework. Standard errors are\ncomputed using sandwich variance estimators that account for\nestimation of the inverse-probability censoring weights\nfollowing Bellach, Kosorok, Rüschendorf and Fine (2019)\n<doi:10.1080/01621459.2017.1401540>.",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.3.3",
  "Config/testthat/edition": "3",
  "VignetteBuilder": "knitr",
  "URL": "https://github.com/abellach/wnpmle",
  "BugReports": "https://github.com/abellach/wnpmle/issues",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-18 22:11:56 UTC",
    "User": "root"
  },
  "Author": "Anna Bellach [aut, cre]",
  "Maintainer": "Anna Bellach <abellach.biostat@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-06-18 17:10:02 UTC",
  "RemoteUrl": "https://github.com/cran/wnpmle",
  "RemoteRef": "HEAD",
  "RemoteSha": "c493d08e09659e5a7857bfd9e646e1bb08df740a",
  "MD5sum": "191791756f2ac32b742a40275ed421b9",
  "_user": "cran",
  "_type": "src",
  "_file": "wnpmle_0.1.2.tar.gz",
  "_fileid": "2d426f443f4e44ea47d2cdb6cc6b50e7fe92251fb06a7e69f67a821667721bad",
  "_filesize": 320045,
  "_sha256": "2d426f443f4e44ea47d2cdb6cc6b50e7fe92251fb06a7e69f67a821667721bad",
  "_created": "2026-06-18T22:11:56.000Z",
  "_published": "2026-06-18T22:15:38.861Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 82244721371,
      "time": 190,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7737080178"
    },
    {
      "job": 82244721354,
      "time": 183,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7737078030"
    },
    {
      "job": 82244136012,
      "time": 231,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7737026598"
    },
    {
      "job": 82244721350,
      "time": 104,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7737056448"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cran/actions/runs/27792322320",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/wnpmle",
  "_commit": {
    "id": "c493d08e09659e5a7857bfd9e646e1bb08df740a",
    "author": "Anna Bellach <abellach.biostat@gmail.com>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.1.2\n",
    "time": 1781802602
  },
  "_maintainer": {
    "name": "Anna Bellach",
    "email": "abellach.biostat@gmail.com",
    "login": "abellach",
    "linkedin": "in/anna-bellach-8554a1134",
    "description": " Ph.D. Biostatistician with expertise in Survival Analysis,  Machine Learning,  Clinical Trials, Semiparametric Models & Mathematical Statistics",
    "uuid": 78665541
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.1.0",
      "role": "Depends"
    },
    {
      "package": "TMB",
      "version": ">= 1.9.0",
      "role": "Imports"
    },
    {
      "package": "survival",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "MASS",
      "role": "Imports"
    },
    {
      "package": "graphics",
      "role": "Imports"
    },
    {
      "package": "grDevices",
      "role": "Imports"
    },
    {
      "package": "testthat",
      "version": ">= 3.0.0",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [
    {
      "week": "2026-25",
      "n": 1
    }
  ],
  "_tags": [
    {
      "name": "0.1.2",
      "date": "2026-06-18"
    }
  ],
  "_stars": 0,
  "_contributors": [
    {
      "user": "abellach",
      "count": 1,
      "uuid": 78665541
    }
  ],
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "followers": 610,
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 0,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/wnpmle"
  },
  "_devurl": "https://github.com/abellach/wnpmle",
  "_searchresults": 0,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/readme.html",
    "extra/readme.md",
    "extra/wnpmle.html",
    "manual.pdf"
  ],
  "_cranurl": false,
  "_releases": [
    {
      "version": "0.1.2",
      "date": "2026-06-18"
    }
  ],
  "_exports": [
    "baseline",
    "bladder_prep",
    "plot_loglik",
    "wnpmle_fit"
  ],
  "_help": [
    {
      "page": "AIC.wnpmle",
      "title": "AIC for wnpmle objects",
      "topics": [
        "AIC.wnpmle"
      ]
    },
    {
      "page": "baseline",
      "title": "Extract the estimated baseline mean function",
      "topics": [
        "baseline"
      ]
    },
    {
      "page": "BIC.wnpmle",
      "title": "BIC for wnpmle objects",
      "topics": [
        "BIC.wnpmle"
      ]
    },
    {
      "page": "bladder_prep",
      "title": "Prepare bladder cancer data for wnpmle analysis",
      "topics": [
        "bladder_prep"
      ]
    },
    {
      "page": "coef.wnpmle",
      "title": "Extract coefficients from a wnpmle object",
      "topics": [
        "coef.wnpmle"
      ]
    },
    {
      "page": "logLik.wnpmle",
      "title": "Log-likelihood for wnpmle objects",
      "topics": [
        "logLik.wnpmle"
      ]
    },
    {
      "page": "plot_loglik",
      "title": "Log-likelihood profile plot for the transformation parameter",
      "topics": [
        "plot_loglik"
      ]
    },
    {
      "page": "plot.wnpmle",
      "title": "Plot method for wnpmle objects",
      "topics": [
        "plot.wnpmle"
      ]
    },
    {
      "page": "predict.wnpmle",
      "title": "Predict marginal mean for new covariate values",
      "topics": [
        "predict.wnpmle"
      ]
    },
    {
      "page": "print.wnpmle",
      "title": "Print method for wnpmle objects",
      "topics": [
        "print.wnpmle"
      ]
    },
    {
      "page": "summary.wnpmle",
      "title": "Summary method for wnpmle objects",
      "topics": [
        "summary.wnpmle"
      ]
    },
    {
      "page": "vcov.wnpmle",
      "title": "Extract variance-covariance matrix from a wnpmle object",
      "topics": [
        "vcov.wnpmle"
      ]
    },
    {
      "page": "wnpmle_fit",
      "title": "Fit Weighted NPMLE for Survival Data with Recurrent or Competing Events",
      "topics": [
        "wnpmle_fit"
      ]
    }
  ],
  "_readme": "https://github.com/cran/wnpmle/raw/HEAD/README.md",
  "_rundeps": [
    "lattice",
    "MASS",
    "Matrix",
    "Rcpp",
    "RcppEigen",
    "survival",
    "TMB"
  ],
  "_vignettes": [
    {
      "source": "wnpmle.Rmd",
      "filename": "wnpmle.html",
      "title": "Getting Started with wnpmle",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "Installation",
        "Quick start: bladder cancer data",
        "Fitting the models",
        "Ghosh-Lin model (Box-Cox, rho = 1)",
        "Proportional odds model (logarithmic, r = 1)",
        "Prediction",
        "Choosing the transformation parameter",
        "Standard errors",
        "S3 methods",
        "References"
      ],
      "created": "2026-06-18 17:10:02",
      "modified": "2026-06-18 17:10:02",
      "commits": 1
    }
  ],
  "_score": 2.6989700043360187,
  "_indexed": false,
  "_nocasepkg": "wnpmle",
  "_universes": [
    "cran",
    "abellach"
  ],
  "_indexurl": "https://abellach.r-universe.dev/wnpmle",
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.1.2",
      "date": "2026-06-18T22:13:58.000Z",
      "distro": "noble",
      "commit": "c493d08e09659e5a7857bfd9e646e1bb08df740a",
      "fileid": "40f9fa297da899de637a2d4bd47a9da75ec575e112207c2ba6e1cf46af4acf16",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/27792322320"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "0.1.2",
      "date": "2026-06-18T22:13:50.000Z",
      "distro": "noble",
      "commit": "c493d08e09659e5a7857bfd9e646e1bb08df740a",
      "fileid": "133cacd68068ead5a4cd98290d36c38ecde8cd9c71abf8e29e79c65e1beaa044",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/27792322320"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.1.2",
      "date": "2026-06-18T22:13:56.000Z",
      "commit": "c493d08e09659e5a7857bfd9e646e1bb08df740a",
      "fileid": "0d887baa8806cbb351e5b2c62f537ded1fab5cf044373d3d033f3bbf6ea0fd88",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cran/actions/runs/27792322320"
    }
  ]
}