{
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  "Title": "Spatial Statistical Modeling and Prediction",
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  "Authors@R": "c(\nperson(given = \"Michael\",\nfamily = \"Dumelle\",\nrole = c(\"aut\", \"cre\"),\nemail = \"Dumelle.Michael@epa.gov\",\ncomment = c(ORCID = \"0000-0002-3393-5529\")),\nperson(given = \"Matt\",\nfamily = \"Higham\",\nrole = \"aut\",\nemail = \"mhigham@stlawu.edu\",\ncomment = c(ORCID = \"0009-0006-4217-625X\")),\nperson(given = \"Ryan A.\",\nfamily = \"Hill\",\nrole = \"ctb\",\nemail = \"hill.ryan@epa.gov\",\ncomment = c(ORCID = \"0000-0001-9583-0426\")),\nperson(given = \"Michael\",\nfamily = \"Mahon\",\nrole = \"ctb\",\nemail = \"Mahon.Michael@epa.gov\",\ncomment = c(ORCID = \"0000-0002-9436-2998\")),\nperson(given = \"Jay M.\",\nfamily = \"Ver Hoef\",\nrole = \"aut\",\nemail = \"jay.verhoef@noaa.gov\",\ncomment = c(ORCID = \"0000-0003-4302-6895\"))\n)",
  "Description": "Fit, summarize, and predict for a variety of spatial\nstatistical models applied to point-referenced and areal\n(lattice) data. Parameters are estimated using various methods.\nAdditional modeling features include anisotropy, non-spatial\nrandom effects, partition factors, big data approaches, and\nmore. Model-fit statistics are used to summarize, visualize,\nand compare models. Predictions at unobserved locations are\nreadily obtainable. For additional details, see Dumelle et al.\n(2023) <doi:10.1371/journal.pone.0282524>.",
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  "URL": "https://usepa.github.io/spmodel/",
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  "Repository": "https://usepa.r-universe.dev",
  "Date/Publication": "2026-01-26 19:59:06 UTC",
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  "Author": "Michael Dumelle [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-3393-5529>),\nMatt Higham [aut] (ORCID: <https://orcid.org/0009-0006-4217-625X>),\nRyan A. Hill [ctb] (ORCID: <https://orcid.org/0000-0001-9583-0426>),\nMichael Mahon [ctb] (ORCID: <https://orcid.org/0000-0002-9436-2998>),\nJay M. Ver Hoef [aut] (ORCID: <https://orcid.org/0000-0003-4302-6895>)",
  "Maintainer": "Michael Dumelle <Dumelle.Michael@epa.gov>",
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      "title": "Compute analysis of variance and likelihood ratio tests of fitted model objects",
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        "augment.spmodel"
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        "AUROC.spgautor",
        "AUROC.spglm"
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      "title": "A caribou forage experiment",
      "topics": [
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    {
      "page": "coef.spmodel",
      "title": "Extract fitted model coefficients",
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        "coef.splm",
        "coef.spmodel",
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      "title": "Confidence intervals for fitted model parameters",
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        "confint.spglm",
        "confint.splm",
        "confint.spmodel"
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        "cooks.distance.spgautor",
        "cooks.distance.spglm",
        "cooks.distance.splm",
        "cooks.distance.spmodel"
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        "covmatrix.spautor",
        "covmatrix.spgautor",
        "covmatrix.spglm",
        "covmatrix.splm"
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        "deviance.spgautor",
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        "deviance.splm",
        "deviance.spmodel"
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      "page": "dispersion_initial",
      "title": "Create a dispersion parameter initial object",
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      "title": "Create a dispersion parameter object",
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      "title": "Compute the empirical autocovariance",
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      "title": "Compute the empirical semivariogram",
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        "plot.esv"
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      "title": "Four Corners State Borders",
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      "title": "Extract model fitted values",
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        "fitted.spgautor",
        "fitted.spglm",
        "fitted.splm",
        "fitted.spmodel",
        "fitted.values.spautor",
        "fitted.values.spgautor",
        "fitted.values.spglm",
        "fitted.values.splm"
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        "formula.spgautor",
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        "formula.spmodel"
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        "glance.spglm",
        "glance.splm",
        "glance.spmodel"
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        "glances.spgautor",
        "glances.spgautor_list",
        "glances.spglm",
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        "glances.splm",
        "glances.splm_list"
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    {
      "page": "hatvalues.spmodel",
      "title": "Compute leverage (hat) values",
      "topics": [
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        "hatvalues.spgautor",
        "hatvalues.spglm",
        "hatvalues.splm",
        "hatvalues.spmodel"
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      "title": "Regression diagnostics",
      "topics": [
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        "influence.spgautor",
        "influence.spglm",
        "influence.splm",
        "influence.spmodel"
      ]
    },
    {
      "page": "labels.spmodel",
      "title": "Find labels from object",
      "topics": [
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        "labels.spgautor",
        "labels.spglm",
        "labels.splm",
        "labels.spmodel"
      ]
    },
    {
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      "title": "National Lakes Assessment Data",
      "topics": [
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    },
    {
      "page": "lake_preds",
      "title": "Lakes Prediction Data",
      "topics": [
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    },
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