{
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  "Package": "npreg",
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  "Title": "Nonparametric Regression via Smoothing Splines",
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  "Date": "2026-03-06",
  "Authors@R": "person(c(\"Nathaniel\", \"E.\"), \"Helwig\", email = \"helwig@umn.edu\", role = c(\"aut\", \"cre\"))",
  "Description": "Multiple and generalized nonparametric regression using\nsmoothing spline ANOVA models and generalized additive models,\nas described in Helwig (2020)\n<doi:10.4135/9781526421036885885>. Includes support for\nGaussian and non-Gaussian responses, smoothers for multiple\ntypes of predictors (including random intercepts), interactions\nbetween smoothers of mixed types, eight different methods for\nsmoothing parameter selection, and flexible tools for\ndiagnostics, inference, and prediction.",
  "License": "GPL (>= 2)",
  "NeedsCompilation": "no",
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    "Date": "2026-06-04 07:32:16 UTC",
    "User": "root"
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  "Author": "Nathaniel E. Helwig [aut, cre]",
  "Maintainer": "Nathaniel E. Helwig <helwig@umn.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-03-06 17:50:07 UTC",
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    "basis.ord",
    "basis.poly",
    "basis.sph",
    "basis.tps",
    "bin.sample",
    "boot",
    "boot.gsm",
    "boot.sm",
    "boot.ss",
    "build_depe",
    "build_depe2",
    "build_rkhs",
    "charkro",
    "check_control",
    "check_family",
    "check_knot",
    "check_type",
    "check_type2",
    "coef.gsm",
    "coef.sm",
    "coef.ss",
    "color.legend",
    "cooks.distance.gsm",
    "cooks.distance.sm",
    "cooks.distance.ss",
    "cov.ratio",
    "cubkern0",
    "cubkern1",
    "cubkern2",
    "deviance.gsm",
    "deviance.sm",
    "deviance.ss",
    "df2lambda",
    "dfbeta.gsm",
    "dfbeta.sm",
    "dfbeta.ss",
    "dfbetas.gsm",
    "dfbetas.sm",
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    "dffits.sm",
    "dffits.ss",
    "diagnostic.plots",
    "family.gsm",
    "fit_gsm",
    "fit_sm",
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    "fitted.sm",
    "fitted.ss",
    "gsm",
    "hatvalues.gsm",
    "hatvalues.sm",
    "hatvalues.ss",
    "influence.gsm",
    "influence.sm",
    "influence.ss",
    "knot1samp",
    "linkern0",
    "linkern1",
    "linkinvd",
    "model.matrix.gsm",
    "model.matrix.sm",
    "model.matrix.ss",
    "msqrt",
    "NegBin",
    "npregStartupMessage",
    "number2color",
    "ordkern",
    "penalty_nom",
    "penalty_ord",
    "penalty_poly",
    "penalty_sph",
    "penalty_tps",
    "penalty.nom",
    "penalty.ord",
    "penalty.poly",
    "penalty.sph",
    "penalty.tps",
    "plot.boot.ss",
    "plot.gsm",
    "plot.sm",
    "plot.ss",
    "plotci",
    "pred_depe",
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    "predict.gsm",
    "predict.sm",
    "predict.ss",
    "print.boot.gsm",
    "print.boot.sm",
    "print.boot.ss",
    "print.gsm",
    "print.sm",
    "print.ss",
    "print.summary.gsm",
    "print.summary.sm",
    "print.summary.ss",
    "psolve",
    "q2fun",
    "q4fun",
    "q6fun",
    "quikern0",
    "quikern1",
    "quikern2",
    "residuals.gsm",
    "residuals.sm",
    "residuals.ss",
    "rexpfam",
    "rowkro",
    "rstandard.gsm",
    "rstandard.sm",
    "rstandard.ss",
    "rstudent.gsm",
    "rstudent.sm",
    "rstudent.ss",
    "sm",
    "smooth.influence",
    "smooth.influence.measures",
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    "summary.gsm",
    "summary.sm",
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    "theta.grad",
    "theta.info",
    "theta.mle",
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    "tune.aic.ss",
    "tune.deep.gsm",
    "tune.deep.sm",
    "tune.gacv.ss",
    "tune.gcv.ss",
    "tune.gsm",
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    "tune.ocv.ss",
    "varimp",
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    "vcov.gsm",
    "vcov.sm",
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    "weights.gsm",
    "weights.sm",
    "weights.ss",
    "wtd.mean",
    "wtd.quantile",
    "wtd.sd",
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      "title": "Bin Sample a Vector, Matrix, or Data Frame",
      "topics": [
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      ]
    },
    {
      "page": "boot",
      "title": "Bootstrap a Fit Smooth",
      "topics": [
        "boot",
        "boot.gsm",
        "boot.sm",
        "boot.ss"
      ]
    },
    {
      "page": "coef",
      "title": "Extract Smooth Model Coefficients",
      "topics": [
        "coef.gsm",
        "coef.sm",
        "coef.ss"
      ]
    },
    {
      "page": "color.legend",
      "title": "Adds Color Legend to Plot Margin",
      "topics": [
        "color.legend"
      ]
    },
    {
      "page": "deviance",
      "title": "Smooth Model Deviance",
      "topics": [
        "deviance.gsm",
        "deviance.sm",
        "deviance.ss"
      ]
    },
    {
      "page": "diagnostic.plots",
      "title": "Plot Nonparametric Regression Diagnostics",
      "topics": [
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      ]
    },
    {
      "page": "fitted",
      "title": "Extract Smooth Model Fitted Values",
      "topics": [
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        "fitted.sm",
        "fitted.ss"
      ]
    },
    {
      "page": "gsm",
      "title": "Fit a Generalized Smooth Model",
      "topics": [
        "family.gsm",
        "gsm"
      ]
    },
    {
      "page": "model.matrix",
      "title": "Construct Design Matrix for Fit Model",
      "topics": [
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        "model.matrix.sm",
        "model.matrix.ss"
      ]
    },
    {
      "page": "msqrt",
      "title": "Matrix (Inverse?) Square Root",
      "topics": [
        "msqrt"
      ]
    },
    {
      "page": "NegBin",
      "title": "Family Function for Negative Binomial",
      "topics": [
        "NegBin"
      ]
    },
    {
      "page": "nominal",
      "title": "Nominal Smoothing Spline Basis and Penalty",
      "topics": [
        "basis.nom",
        "basis_nom",
        "nominal",
        "penalty.nom",
        "penalty_nom"
      ]
    },
    {
      "page": "number2color",
      "title": "Map Numbers to Colors",
      "topics": [
        "number2color"
      ]
    },
    {
      "page": "ordinal",
      "title": "Ordinal Smoothing Spline Basis and Penalty",
      "topics": [
        "basis.ord",
        "basis_ord",
        "ordinal",
        "penalty.ord",
        "penalty_ord"
      ]
    },
    {
      "page": "plot.gsm",
      "title": "Plot Effects for Generalized Smooth Model Fits",
      "topics": [
        "plot.gsm"
      ]
    },
    {
      "page": "plot.sm",
      "title": "Plot Effects for Smooth Model Fits",
      "topics": [
        "plot.sm"
      ]
    },
    {
      "page": "plot.ss",
      "title": "Plot method for Smoothing Spline Fit and Bootstrap",
      "topics": [
        "plot.boot.ss",
        "plot.ss"
      ]
    },
    {
      "page": "plotci",
      "title": "Generic X-Y Plotting with Confidence Intervals",
      "topics": [
        "plotci"
      ]
    },
    {
      "page": "polynomial",
      "title": "Polynomial Smoothing Spline Basis and Penalty",
      "topics": [
        "basis.poly",
        "basis_poly",
        "penalty.poly",
        "penalty_poly",
        "polynomial"
      ]
    },
    {
      "page": "predict.gsm",
      "title": "Predict method for Generalized Smooth Model Fits",
      "topics": [
        "predict.gsm"
      ]
    },
    {
      "page": "predict.sm",
      "title": "Predict method for Smooth Model Fits",
      "topics": [
        "predict.sm"
      ]
    },
    {
      "page": "predict.ss",
      "title": "Predict method for Smoothing Spline Fits",
      "topics": [
        "predict.ss"
      ]
    },
    {
      "page": "psolve",
      "title": "Pseudo-Solve a System of Equations",
      "topics": [
        "psolve"
      ]
    },
    {
      "page": "residuals",
      "title": "Extract Model Residuals",
      "topics": [
        "residuals.gsm",
        "residuals.sm",
        "residuals.ss"
      ]
    },
    {
      "page": "sm",
      "title": "Fit a Smooth Model",
      "topics": [
        "sm"
      ]
    },
    {
      "page": "smooth.influence",
      "title": "Nonparametric Regression Diagnostics",
      "topics": [
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        "influence.sm",
        "influence.ss",
        "smooth.influence"
      ]
    },
    {
      "page": "smooth.influence.measures",
      "title": "Nonparametric Regression Deletion Diagnostics",
      "topics": [
        "cooks.distance.gsm",
        "cooks.distance.sm",
        "cooks.distance.ss",
        "cov.ratio",
        "dfbeta.gsm",
        "dfbeta.sm",
        "dfbeta.ss",
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        "dfbetas.sm",
        "dfbetas.ss",
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        "dffits.ss",
        "hatvalues.gsm",
        "hatvalues.sm",
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        "rstandard.gsm",
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        "rstandard.ss",
        "rstudent.gsm",
        "rstudent.sm",
        "rstudent.ss",
        "smooth.influence.measures"
      ]
    },
    {
      "page": "spherical",
      "title": "Spherical Spline Basis and Penalty",
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        "basis_sph",
        "penalty.sph",
        "penalty_sph",
        "spherical"
      ]
    },
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      "page": "StartupMessage",
      "title": "Startup Message for npreg",
      "topics": [
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        "StartupMessage"
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        "print.summary.sm",
        "print.summary.ss",
        "summary",
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        "summary.sm",
        "summary.ss"
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      "page": "thinplate",
      "title": "Thin Plate Spline Basis and Penalty",
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        "basis_tps",
        "penalty.tps",
        "penalty_tps",
        "thinplate"
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      "concept": [
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      "page": "varinf",
      "title": "Variance Inflation Factors",
      "concept": [
        "multicollinearity"
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    {
      "page": "vcov",
      "title": "Calculate Variance-Covariance Matrix for a Fitted Smooth Model",
      "topics": [
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        "vcov.sm",
        "vcov.ss"
      ]
    },
    {
      "page": "weights",
      "title": "Extract Smooth Model Weights",
      "topics": [
        "weights.gsm",
        "weights.sm",
        "weights.ss"
      ]
    },
    {
      "page": "wtd.mean",
      "title": "Weighted Arithmetic Mean",
      "topics": [
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      "title": "Weighted Quantiles",
      "topics": [
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    },
    {
      "page": "wtd.var",
      "title": "Weighted Variance and Standard Deviation",
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        "wtd.var"
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