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  "Description": "Common utilities used in other MOSAIC-family packages are\ncollected here.",
  "License": "GPL (>=2)",
  "LazyLoad": "yes",
  "URL": "https://github.com/ProjectMOSAIC/mosaicCore",
  "BugReports": "https://github.com/ProjectMOSAIC/mosaicCore/issues",
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  "Date/Publication": "2025-12-03 01:55:31 UTC",
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    "User": "root"
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  "Author": "Randall Pruim [aut, cre],\nDaniel T. Kaplan [aut],\nNicholas J. Horton [aut]",
  "Maintainer": "Randall Pruim <rpruim@calvin.edu>",
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    "name": "Project MOSAIC",
    "followers": 20,
    "description": "Project MOSAIC is a community of educators working to develop a new way to introduce mathematics, statistics, computation and modeling."
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    "ci.median",
    "ci.prop",
    "ci.sd",
    "columns",
    "compare",
    "condition",
    "count",
    "counts",
    "coverage",
    "df_stats",
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    "ediff",
    "evalFormula",
    "evalSubFormula",
    "fit_distr_fun",
    "formularise",
    "ilogit",
    "infer_transformation",
    "inspect",
    "joinFrames",
    "lhs",
    "logical2factor",
    "logit",
    "make_df",
    "makeFun",
    "modelVars",
    "mosaic_count",
    "mosaic_formula",
    "mosaic_formula_q",
    "mosaic_tally",
    "msummary",
    "n_missing",
    "n_not_missing",
    "n_total",
    "na.warn",
    "named",
    "named_among",
    "nice_names",
    "operator",
    "parse.formula",
    "perc",
    "percs",
    "prop",
    "prop1",
    "props",
    "reop_formula",
    "rhs",
    "rhs_or_expr",
    "rows",
    "tally",
    "unnamed",
    "vector2df"
  ],
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      "page": "ashplot",
      "title": "Compute knot points of an average shifted histogram",
      "topics": [
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      ]
    },
    {
      "page": "coef",
      "title": "Extract coefficients from a function",
      "topics": [
        "coef",
        "coef.function"
      ]
    },
    {
      "page": "columns",
      "title": "return a vector of row or column indices",
      "topics": [
        "columns",
        "rows"
      ]
    },
    {
      "page": "compare",
      "title": "Campare two numeric vectors",
      "topics": [
        "compare"
      ]
    },
    {
      "page": "props",
      "title": "Compute all proportions or counts",
      "topics": [
        "counts",
        "counts.default",
        "counts.factor",
        "counts.formula",
        "percs",
        "props"
      ]
    },
    {
      "page": "interval_statistics",
      "title": "Interval statistics",
      "topics": [
        "ci.mean",
        "ci.median",
        "ci.prop",
        "ci.sd",
        "coverage",
        "interval_statistics"
      ]
    },
    {
      "page": "df_stats",
      "title": "Calculate statistics for \"response\" variables",
      "topics": [
        "df_stats"
      ]
    },
    {
      "page": "dfapply",
      "title": "apply-type function for data frames",
      "topics": [
        "dfapply"
      ]
    },
    {
      "page": "ediff",
      "title": "Lagged Differences with equal length",
      "topics": [
        "ediff"
      ]
    },
    {
      "page": "evalFormula",
      "title": "Evaluate a formula",
      "topics": [
        "evalFormula"
      ]
    },
    {
      "page": "evalSubFormula",
      "title": "Evaluate a part of a formula",
      "topics": [
        "evalSubFormula"
      ]
    },
    {
      "page": "fit_distr_fun",
      "title": "Fit a distribution to data and return a function",
      "topics": [
        "fit_distr_fun"
      ]
    },
    {
      "page": "formularise",
      "title": "Convert lazy objects into formulas",
      "topics": [
        "formularise"
      ]
    },
    {
      "page": "infer_transformation",
      "title": "Infer a Back-Transformation",
      "topics": [
        "infer_transformation"
      ]
    },
    {
      "page": "inspect",
      "title": "Inspect objects",
      "topics": [
        "inspect",
        "inspect.character",
        "inspect.data.frame",
        "inspect.Date",
        "inspect.factor",
        "inspect.list",
        "inspect.logical",
        "inspect.numeric",
        "inspect.POSIXt",
        "print.inspected_data_frame"
      ]
    },
    {
      "page": "joinFrames",
      "title": "Join data frames",
      "topics": [
        "joinFrames",
        "joinTwoFrames"
      ]
    },
    {
      "page": "logical2factor",
      "title": "Convert logical vector into factor",
      "topics": [
        "logical2factor",
        "logical2factor.data.frame",
        "logical2factor.default"
      ]
    },
    {
      "page": "logit",
      "title": "Logit and inverse logit functions",
      "topics": [
        "ilogit",
        "logit"
      ]
    },
    {
      "page": "make_df",
      "title": "Convert to a data frame",
      "topics": [
        "make_df",
        "make_df.default",
        "make_df.list",
        "make_df.matrix",
        "make_df.numeric"
      ]
    },
    {
      "page": "makeFun",
      "title": "Create a function from a formula",
      "topics": [
        "makeFun",
        "makeFun.formula",
        "makeFun.function",
        "makeFun.glm",
        "makeFun.lm",
        "makeFun.nls"
      ]
    },
    {
      "page": "modelVars",
      "title": "extract predictor variables from a model",
      "topics": [
        "modelVars"
      ]
    },
    {
      "page": "mosaicformula",
      "title": "Convert formulas into standard shapes",
      "topics": [
        "mosaic_formula",
        "mosaic_formula_q"
      ]
    },
    {
      "page": "mosaic_tally",
      "title": "Internal tally methods",
      "topics": [
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        "mosaic_tally"
      ]
    },
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      "topics": [
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        "n_not_missing",
        "n_total"
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        "named_among",
        "unnamed"
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      "page": "nicenames",
      "title": "Nice names",
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        "condition.formula",
        "condition.parsedFormula",
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        "lhs.formula",
        "lhs.parsedFormula",
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        "operator.formula",
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      "topics": [
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        "msummary.default",
        "msummary.glm",
        "msummary.lm",
        "print.msummary.glm",
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        "prop",
        "prop1"
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        "mosaic_tally.formula",
        "mosaic_tally.tbl",
        "tally"
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