{
  "_id": "6a1f2feeb401979e73427687",
  "Package": "SpatialExtremes",
  "Version": "2.1-0",
  "Date": "2022-04-19",
  "Title": "Modelling Spatial Extremes",
  "Authors@R": "c(person(\"Mathieu\", \"Ribatet\", role = c(\"aut\", \"cre\"),\nemail = \"mathieu.ribatet@ec-nantes.fr\"),\nperson(\"Richard\", \"Singleton\", role = \"ctb\"),\nperson(\"R Core team\", role = \"ctb\"))",
  "Description": "Tools for the statistical modelling of spatial extremes\nusing max-stable processes, copula or Bayesian hierarchical\nmodels. More precisely, this package allows (conditional)\nsimulations from various parametric max-stable models, analysis\nof the extremal spatial dependence, the fitting of such\nprocesses using composite likelihoods or least square (simple\nmax-stable processes only), model checking and selection and\nprediction. Other approaches (although not completely in\nagreement with the extreme value theory) are available such as\nthe use of (spatial) copula and Bayesian hierarchical models\nassuming the so-called conditional assumptions. The latter\napproaches is handled through an (efficient) Gibbs sampler.\nSome key references: Davison et al. (2012)\n<doi:10.1214/11-STS376>, Padoan et al. (2010)\n<doi:10.1198/jasa.2009.tm08577>, Dombry et al. (2013)\n<doi:10.1093/biomet/ass067>.",
  "License": "GPL (>= 2)",
  "URL": "http://spatialextremes.r-forge.r-project.org/",
  "Repository": "https://r-forge.r-universe.dev",
  "Date/Publication": "2024-04-30 09:59:04 UTC",
  "RemoteUrl": "https://github.com/r-forge/spatialextremes",
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  "Packaged": {
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  "Author": "Mathieu Ribatet [aut, cre],\nRichard Singleton [ctb],\nR Core team [ctb]",
  "Maintainer": "Mathieu Ribatet <mathieu.ribatet@ec-nantes.fr>",
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    "author": "mathieu_ribatet (Mathieu Ribatet) <mathieu.ribatet@ec-nantes.fr>",
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    "message": "Update related to some modification in the C header file\n\ngit-svn-id: svn://svn.r-forge.r-project.org/svnroot/spatialextremes@893 edb9625f-4e0d-4859-8d74-9fd3b1da38cb\n",
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      "name": "wind",
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  "_help": [
    {
      "page": "anova",
      "title": "Anova Tables",
      "topics": [
        "anova",
        "anova.maxstab",
        "anova.spatgev"
      ]
    },
    {
      "page": "concprob",
      "title": "Pairwise empirical and extremal concurrence probabilities",
      "topics": [
        "concprob"
      ]
    },
    {
      "page": "concurrencemap",
      "title": "Maps of concurrence probabilities/expected concurrence cell area",
      "topics": [
        "concurrencemap"
      ]
    },
    {
      "page": "condmap",
      "title": "Produces a conditional 2D map from a fitted max-stable process",
      "topics": [
        "condmap"
      ]
    },
    {
      "page": "condrgp",
      "title": "Conditional simulation of Gaussian random fields",
      "topics": [
        "condrgp"
      ]
    },
    {
      "page": "condrmaxlin",
      "title": "Conditional simulation of max-linear random fields",
      "topics": [
        "condrmaxlin"
      ]
    },
    {
      "page": "condrmaxstab",
      "title": "Conditional simulation of max-stable processes",
      "topics": [
        "condrmaxstab"
      ]
    },
    {
      "page": "covariance",
      "title": "Defines and computes covariance functions",
      "topics": [
        "covariance"
      ]
    },
    {
      "page": "cv",
      "title": "Estimates the penalty coefficient from the cross-validation criterion",
      "topics": [
        "cv"
      ]
    },
    {
      "page": "DIC",
      "title": "Deviance Information Criterion",
      "topics": [
        "DIC"
      ]
    },
    {
      "page": "distances",
      "title": "Computes distance between pairs of locations",
      "topics": [
        "distance"
      ]
    },
    {
      "page": "extcoeff",
      "title": "Plots the extremal coefficient",
      "topics": [
        "extcoeff"
      ]
    },
    {
      "page": "fitcopula",
      "title": "Fit a copula-based model to spatial extremes",
      "topics": [
        "fitcopula"
      ]
    },
    {
      "page": "fitcovariance",
      "title": "Estimates the covariance function for the Schlather's model",
      "topics": [
        "fitcovariance"
      ]
    },
    {
      "page": "fitcovmat",
      "title": "Estimates the covariance matrix for the Smith's model",
      "topics": [
        "fitcovmat"
      ]
    },
    {
      "page": "extcoeffemp",
      "title": "Non parametric estimators of the extremal coefficient function",
      "topics": [
        "fitextcoeff"
      ]
    },
    {
      "page": "fitmaxstab",
      "title": "Fits a max-stable process to data",
      "topics": [
        "fitmaxstab"
      ]
    },
    {
      "page": "fitspatgev",
      "title": "MLE for a spatial GEV model",
      "topics": [
        "fitspatgev"
      ]
    },
    {
      "page": "fmadogram",
      "title": "Computes the F-madogram",
      "topics": [
        "fmadogram"
      ]
    },
    {
      "page": "gcv",
      "title": "Estimates the penalty coefficient from the generalized cross-validation criterion",
      "topics": [
        "gcv"
      ]
    },
    {
      "page": "GEV",
      "title": "The Generalized Extreme Value Distribution",
      "topics": [
        "dgev",
        "pgev",
        "qgev",
        "rgev"
      ]
    },
    {
      "page": "GPD",
      "title": "The Generalized Pareto Distribution",
      "topics": [
        "dgpd",
        "pgpd",
        "qgpd",
        "rgpd"
      ]
    },
    {
      "page": "gev2frech",
      "title": "Transforms GEV data to unit Frechet ones and vice versa",
      "topics": [
        "frech2gev",
        "gev2frech"
      ]
    },
    {
      "page": "kriging",
      "title": "Simple kriging interpolation",
      "topics": [
        "kriging"
      ]
    },
    {
      "page": "latentVariable",
      "title": "Bayesian hierarchical models for spatial extremes",
      "topics": [
        "latent"
      ]
    },
    {
      "page": "lmadogram",
      "title": "Computes the lambda-madogram",
      "topics": [
        "lmadogram"
      ]
    },
    {
      "page": "logLik",
      "title": "Extracts Log-Likelihood",
      "topics": [
        "logLik",
        "logLik.copula",
        "logLik.maxstab"
      ]
    },
    {
      "page": "lsmaxstab",
      "title": "Estimates the spatial dependence parameter of a max-stable process by minimizing least squares.",
      "topics": [
        "lsmaxstab"
      ]
    },
    {
      "page": "madogram",
      "title": "Computes madograms",
      "topics": [
        "madogram"
      ]
    },
    {
      "page": "map",
      "title": "Produces a 2D map from a fitted max-stable process",
      "topics": [
        "map"
      ]
    },
    {
      "page": "map.latent",
      "title": "Two dimensional map from a Bayesian hierarchical model",
      "topics": [
        "map.latent"
      ]
    },
    {
      "page": "univfit",
      "title": "Fits univariate extreme value distributions to data",
      "topics": [
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        "gpdmle"
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    },
    {
      "page": "modeldef",
      "title": "Define a model for the spatial behaviour of the GEV parameters",
      "topics": [
        "modeldef",
        "modeldef.lm",
        "modeldef.rb"
      ]
    },
    {
      "page": "plot.copula",
      "title": "Model checking of a fitted copula based model.",
      "topics": [
        "plot.copula"
      ]
    },
    {
      "page": "plot.maxstab",
      "title": "Model checking of a fitted max-stable model",
      "topics": [
        "plot.maxstab"
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    },
    {
      "page": "predict",
      "title": "Prediction of the marginal parameters for various models",
      "topics": [
        "predict",
        "predict.copula",
        "predict.maxstab",
        "predict.pspline2",
        "predict.spatgev"
      ]
    },
    {
      "page": "print",
      "title": "Printing objects of classes defined in the SpatialExtreme packages",
      "topics": [
        "print",
        "print.copula",
        "print.latent",
        "print.maxstab",
        "print.pspline2",
        "print.spatgev"
      ]
    },
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