{
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  "Package": "PVAClone",
  "Type": "Package",
  "Title": "Population Viability Analysis with Data Cloning",
  "Version": "0.1-8",
  "Date": "2025-07-12",
  "Authors@R": "c(person(given = \"Khurram\",\nfamily = \"Nadeem\",\nrole = \"aut\"),\nperson(given = \"Peter\",\nfamily = \"Solymos\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-7337-1740\"),\nemail = \"psolymos@gmail.com\"))",
  "Maintainer": "Peter Solymos <psolymos@gmail.com>",
  "Description": "Likelihood based population viability analysis in the\npresence of observation error and missing data. The package can\nbe used to fit, compare, predict, and forecast various growth\nmodel types using data cloning.",
  "License": "GPL-2",
  "SystemRequirements": "JAGS (>= 3.0.0)",
  "URL": "https://github.com/psolymos/PVAClone",
  "BugReports": "https://github.com/psolymos/PVAClone/issues",
  "LazyLoad": "yes",
  "LazyData": "true",
  "Config/pak/sysreqs": "make jags",
  "Repository": "https://psolymos.r-universe.dev",
  "Date/Publication": "2025-07-13 18:08:16 UTC",
  "RemoteUrl": "https://github.com/psolymos/PVAClone",
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    "User": "root"
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  "Author": "Khurram Nadeem [aut],\nPeter Solymos [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-7337-1740>)",
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  "_topics": [
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    "cpp"
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
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      "date": "2012-08-25"
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      "date": "2014-05-19"
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      "date": "2024-01-23"
    },
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      "date": "2025-07-13"
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    "coef",
    "confint",
    "diagn_scale",
    "fancyPVAmodel",
    "generateLatent",
    "gompertz",
    "model.select",
    "print.pvaModelSelect",
    "pva",
    "pva.llr",
    "ricker",
    "summary",
    "thetalogistic",
    "thetalogistic_D",
    "ts_index",
    "vcov"
  ],
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      "title": "Paramecium abundance time series",
      "object": "paurelia",
      "class": [
        "numeric"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "redstart",
      "title": "Abundance time series of American Redstart",
      "object": "redstart",
      "class": [
        "numeric"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "songsparrow",
      "title": "Abundance time series of Song Sparrow",
      "object": "songsparrow",
      "class": [
        "numeric"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "PVAClone-package",
      "title": "Population Viability Analysis with Data Cloning",
      "topics": [
        "PVAClone-package",
        "PVA",
        "Pva",
        "PVAClone",
        "pvaclone"
      ]
    },
    {
      "page": "fancyPVAmodel",
      "title": "Print fancy model names in summaries",
      "topics": [
        "fancyPVAmodel"
      ]
    },
    {
      "page": "generateLatent",
      "title": "Generate latent variable",
      "topics": [
        "generateLatent"
      ]
    },
    {
      "page": "growthmodels",
      "title": "Growth models",
      "topics": [
        "bevertonholt",
        "gompertz",
        "growthmodels",
        "ricker",
        "thetalogistic",
        "thetalogistic_D"
      ]
    },
    {
      "page": "internals",
      "title": "Internal functions",
      "topics": [
        "internal-functions",
        "Internals",
        "internals",
        "PVAClone-internals",
        "ts_index"
      ]
    },
    {
      "page": "model.select",
      "title": "Model selection for 'pva' objects",
      "topics": [
        "model.select",
        "print.pvaModelSelect",
        "pva.llr"
      ]
    },
    {
      "page": "paurelia",
      "title": "Paramecium abundance time series",
      "topics": [
        "paurelia"
      ]
    },
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      "page": "pva",
      "title": "Population Viability Analysis",
      "topics": [
        "diagn_scale",
        "pva"
      ]
    },
    {
      "page": "pva-class",
      "title": "Class '\"pva\"'",
      "topics": [
        "pva-class"
      ]
    },
    {
      "page": "pva-methods",
      "title": "Methods for 'pva' objects",
      "topics": [
        "coef,pva-method",
        "confint,pva-method",
        "summary,pva-method",
        "vcov,pva-method"
      ]
    },
    {
      "page": "pvamodel-class",
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      ]
    },
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