{
  "_id": "6a1f24deb401979e73420e86",
  "Package": "extRemes",
  "Version": "2.2-1",
  "Date": "2025-05-16",
  "Title": "Extreme Value Analysis",
  "Authors@R": "person(given = \"Eric\",\nfamily = \"Gilleland\",\nrole = c(\"aut\", \"cre\"),\nemail = \"eric.gilleland@colostate.edu\",\ncomment = c( ORCID = \"0000-0002-8058-7643\" ))",
  "Author": "Eric Gilleland [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-8058-7643>)",
  "Maintainer": "Eric Gilleland <eric.gilleland@colostate.edu>",
  "Description": "General functions for performing extreme value analysis.\nIn particular, allows for inclusion of covariates into the\nparameters of the extreme-value distributions, as well as\nestimation through MLE, L-moments, generalized (penalized) MLE\n(GMLE), as well as Bayes.  Inference methods include parametric\nnormal approximation, profile-likelihood, Bayes, and\nbootstrapping.  Some bivariate functionality and dependence\nchecking (e.g., auto-tail dependence function plot, extremal\nindex estimation) is also included.  For a tutorial, see\nGilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for\nbootstrapping, please see Gilleland (2020) <doi:\n10.1175/JTECH-D-20-0070.1>.",
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  "Date/Publication": "2025-05-16 19:00:02 UTC",
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    {
      "page": "extRemes-package",
      "title": "extRemes - Weather and Climate Applications of Extreme Value Analysis (EVA)",
      "topics": [
        "extRemes-package",
        "extRemes"
      ]
    },
    {
      "page": "atdf",
      "title": "Auto-Tail Dependence Function",
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        "plot.atdf"
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      "title": "Estimate Bayes Factor",
      "topics": [
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        "blockmaxxer.vector"
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      "title": "European Climate Assessment and Dataset",
      "topics": [
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      "title": "Confidence Intervals",
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        "ci.fevd.bayesian",
        "ci.fevd.lmoments",
        "ci.fevd.mle"
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    {
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      "title": "Confidence/Credible Intervals for Effective Return Levels",
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      "title": "Hurricane Damage Data",
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    {
      "page": "datagrabber",
      "title": "Get Original Data from an R Object",
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        "datagrabber.extremalindex",
        "datagrabber.fevd"
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    {
      "page": "decluster",
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      "topics": [
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        "decluster.data.frame",
        "decluster.default",
        "decluster.intervals",
        "decluster.runs",
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