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  "Version": "0.2.5",
  "Date": "2023-05-05",
  "Title": "Modeling Multivariate Origins Determinants - Evolutionary\nLineages in Ecology",
  "Author": "David M Schruth",
  "Maintainer": "David M Schruth <dschruth@anthropoidea.org>",
  "Description": "Perform multivariate modeling of evolved traits, with\nspecial attention to understanding the interplay of the\nmulti-factorial determinants of their origins in complex\necological settings (Stephens, 2007\n<doi:10.1016/j.tree.2006.12.003>). This software primarily\nconcentrates on phylogenetic regression analysis, enabling\nimplementation of tree transformation averaging and\nvisualization functionality. Functions additionally support\ninformation theoretic approaches (Grueber, 2011\n<doi:10.1111/j.1420-9101.2010.02210.x>; Garamszegi, 2011\n<doi:10.1007/s00265-010-1028-7>) such as model averaging and\nselection of phylogenetic models. Accessory functions are also\nimplemented for coef standardization (Cade 2015), selection\nuncertainty, and variable importance (Burnham & Anderson 2000).\nThere are other numerous functions for visualizing confounded\nvariables, plotting phylogenetic trees, as well as reporting\nand exporting modeling results. Lastly, as challenges to\necology are inherently multifarious, and therefore often\nmulti-dataset, this package features several functions to\nsupport the identification, interpolation, merging, and\nupdating of missing data and outdated nomenclature.",
  "License": "Apache License",
  "LazyLoad": "yes",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-05 10:04:22 UTC",
    "User": "root"
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  "Repository": "https://dranthropoid.r-universe.dev",
  "Date/Publication": "2023-05-17 06:10:02 UTC",
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    "count.mod.vars",
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    "pgls.print",
    "pgls.report",
    "pgls.wrap",
    "plot.confound.grid",
    "plot.pgls.iters",
    "plot.pgls.R2AIC",
    "plot.transformed.phylo",
    "plot.xy.ab.p",
    "select.best.models",
    "sparge.modsel",
    "trim.phylo",
    "variable.importance",
    "weight.IC"
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        "variable.importance"
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    },
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      "page": "calc.q2n.ratio",
      "title": "Calculate the ratio of fit predictor variables to sample size",
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    },
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      "title": "Include all variables except ...",
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    {
      "page": "comp.data",
      "title": "Comparative Data",
      "topics": [
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      ]
    },
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      "title": "Find data being dropped by mismatches to the tree",
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    },
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      "title": "Correct AIC",
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    },
    {
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      "title": "Count the predictor variables in a model",
      "topics": [
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      ]
    },
    {
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      "title": "Count all possible model combinations",
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    {
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      "title": "Drop any rows with NA values",
      "topics": [
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      "topics": [
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    },
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      ]
    },
    {
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      "title": "Get the outcome variable from a model string",
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    },
    {
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      "title": "Get model variable names",
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    },
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    },
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      "topics": [
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    },
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    },
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      ]
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      "title": "Report missing values in a dataframe",
      "topics": [
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      ]
    },
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      "topics": [
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    },
    {
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      "title": "Report PGLS results as a table",
      "topics": [
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    },
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      "page": "pgls.wrap",
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