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  "Title": "Surrogate Residuals for Ordinal and General Regression Models",
  "Description": "An implementation of the surrogate approach to residuals\nand diagnostics for ordinal and general regression models; for\ndetails, see Liu and Zhang (2017,\n<doi:https://doi.org/10.1080/01621459.2017.1292915>) and\nGreenwell et al. (2017,\n<https://journal.r-project.org/archive/2018/RJ-2018-004/index.html>).\nThese residuals can be used to construct standard residual\nplots for model diagnostics (e.g., residual-vs-fitted value\nplots, residual-vs-covariate plots, Q-Q plots, etc.). The\npackage also provides 'plot' methods for producing standard\ndiagnostic plots using lightweight base R graphics (via\n'tinyplot'). The package currently supports cumulative link\nmodels from packages 'MASS', 'ordinal', 'rms', and 'VGAM'.\nSupport for binary regression models using the standard 'glm'\nfunction is also available.",
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  "Authors@R": "c(\nperson(\"Brandon\", \"Greenwell\",\nemail = \"greenwell.brandon@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Andrew\", \"McCarthy\",\nemail = \"mccarthyan@gmail.com\",\nrole = c(\"aut\")),\nperson(\"Boehmke\", \"Bradley\",\nemail = \"bradleyboehmke@gmail.com\",\nrole = c(\"aut\")),\nperson(\"Liz\", \"Glaser\",\nemail = \"liz.glaser@gmail.com\",\nrole = c(\"ctb\"))\n)",
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  "URL": "https://github.com/bgreenwell/sure,\nhttps://bgreenwell.github.io/sure/,\nhttps://bgreenwell.r-universe.dev/sure",
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  "Date/Publication": "2026-07-07 02:46:58 UTC",
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  "Maintainer": "Brandon Greenwell <greenwell.brandon@gmail.com>",
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        "plot.orm",
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        "resids.default",
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      "title": "Simulate Data for Diagnostic Plots",
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        "Surrogate residuals",
        "Jittering for general models",
        "Bootstrapping",
        "Surrogate residuals in R",
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        "Obtain the SBS/probability-scale residuals",
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        "Checking the proportionality assumption",
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