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  "Package": "MASSExtra",
  "Type": "Package",
  "Title": "Some 'MASS' Enhancements",
  "Version": "1.2.2",
  "Author": "Bill Venables",
  "Maintainer": "Bill Venables <bill.venables@gmail.com>",
  "Description": "Some enhancements, extensions and additions to the\nfacilities of the recommended 'MASS' package that are useful\nmainly for teaching purposes, with more convenient default\nsettings and user interfaces. Key functions from 'MASS' are\nimported and re-exported to avoid masking conflicts.  In\naddition we provide some additional functions mainly used to\nillustrate coding paradigms and techniques, such as\nGramm-Schmidt orthogonalisation and generalised eigenvalue\nproblems.",
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    "add_term",
    "addterm",
    "as_complex",
    "avoid",
    "bc",
    "bc_inv",
    "box_cox",
    "boxcox",
    "bs",
    "cm2in",
    "default_test",
    "drop_term",
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    "eigen2",
    "fractions",
    "GIC",
    "ginv",
    "givens_orth",
    "glm.convert",
    "glm.nb",
    "glmmPQL",
    "gs_orth",
    "gs_orth_modified",
    "hr_levels",
    "in2cm",
    "in2mm",
    "in2usr",
    "isoMDS",
    "kde_1d",
    "kde_2d",
    "kde2d",
    "lambda",
    "lda",
    "lm.gls",
    "logtrans",
    "lqs",
    "mean_c",
    "mm2in",
    "mvrnorm",
    "negative.binomial",
    "ns",
    "Null",
    "polr",
    "qda",
    "rlm",
    "rnegbin",
    "sammon",
    "stdres",
    "step_AIC",
    "step_BIC",
    "step_down",
    "step_GIC",
    "stepAIC",
    "studres",
    "theta.md",
    "theta.ml",
    "theta.mm",
    "ucv",
    "usr2in",
    "var_c",
    "vcovx",
    "which_tri",
    "width.SJ",
    "zq",
    "zr",
    "zs",
    "zu"
  ],
  "_datasets": [
    {
      "name": "Boston",
      "title": "Boston",
      "object": "Boston",
      "class": [
        "data.frame"
      ],
      "fields": [
        "crim",
        "zn",
        "indus",
        "chas",
        "nox",
        "rm",
        "age",
        "dis",
        "rad",
        "tax",
        "ptratio",
        "black",
        "lstat",
        "medv"
      ],
      "rows": 506,
      "table": true,
      "tojson": true
    },
    {
      "name": "Cars93",
      "title": "Cars93",
      "object": "Cars93",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Manufacturer",
        "Model",
        "Type",
        "Min.Price",
        "Price",
        "Max.Price",
        "MPG.city",
        "MPG.highway",
        "AirBags",
        "DriveTrain",
        "Cylinders",
        "EngineSize",
        "Horsepower",
        "RPM",
        "Rev.per.mile",
        "Man.trans.avail",
        "Fuel.tank.capacity",
        "Passengers",
        "Length",
        "Wheelbase",
        "Width",
        "Turn.circle",
        "Rear.seat.room",
        "Luggage.room",
        "Weight",
        "Origin",
        "Make"
      ],
      "rows": 93,
      "table": true,
      "tojson": true
    },
    {
      "name": "quine",
      "title": "quine",
      "object": "quine",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Eth",
        "Sex",
        "Age",
        "Lrn",
        "Days"
      ],
      "rows": 146,
      "table": true,
      "tojson": true
    },
    {
      "name": "whiteside",
      "title": "whiteside",
      "object": "whiteside",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Insul",
        "Temp",
        "Gas"
      ],
      "rows": 56,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "dot-normalise",
      "title": "Normalise a vector",
      "topics": [
        ".normalise"
      ]
    },
    {
      "page": "as_complex",
      "title": "Coerce to complex",
      "topics": [
        "as_complex",
        "as_complex,missing,numeric-method",
        "as_complex,numeric,missing-method",
        "as_complex,numeric,numeric-method",
        "as_complex,xy,missing-method"
      ]
    },
    {
      "page": "avoid",
      "title": "Avoid overlaps",
      "topics": [
        "avoid",
        "avoid,numeric-method",
        "avoid,xy-method"
      ]
    },
    {
      "page": "bc",
      "title": "Box-Cox transform",
      "topics": [
        "bc"
      ]
    },
    {
      "page": "bc_inv",
      "title": "Box-Cox transform inverse",
      "topics": [
        "bc_inv"
      ]
    },
    {
      "page": "Boston",
      "title": "Boston",
      "topics": [
        "Boston"
      ]
    },
    {
      "page": "box_cox",
      "title": "Box-cox constructor function",
      "topics": [
        "box_cox",
        "box_cox,formula-method",
        "box_cox,lm-method",
        "plot.box_cox",
        "print.box_cox"
      ]
    },
    {
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      "title": "Cars93",
      "topics": [
        "Cars93"
      ]
    },
    {
      "page": "default_test",
      "title": "Guess the default test",
      "topics": [
        "default_test",
        "default_test.default",
        "default_test.glm",
        "default_test.glmerMod",
        "default_test.lm",
        "default_test.lmerMod",
        "default_test.multinom",
        "default_test.negbin",
        "default_test.polr"
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    },
    {
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      "title": "Generalized eigenvalue problem",
      "topics": [
        "eigen2"
      ]
    },
    {
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      "title": "Intermediate Information Criterion",
      "topics": [
        "GIC"
      ]
    },
    {
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      "title": "Givens orthogonalisation",
      "topics": [
        "givens_orth"
      ]
    },
    {
      "page": "gs_orth_modified",
      "title": "Gram-Schmidt orthogonalization",
      "topics": [
        "gs_orth",
        "gs_orth_modified"
      ]
    },
    {
      "page": "hr_levels",
      "title": "#' @rdname kde_1d #' @export kernelBiweight <- function(x, mean = 0, sd = 1) h <- sqrt(7)*sd ifelse((z <- abs(x-mean)) < h, 15/16*(1 - (z/h)^2)^2/h, 0)",
      "topics": [
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        "hr_levels.default",
        "hr_levels.kde_2d"
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    },
    {
      "page": "kde_1d",
      "title": "One-dimensional Kernel Density Estimate",
      "topics": [
        "kde_1d",
        "plot.kde_1d",
        "print.kde_1d"
      ]
    },
    {
      "page": "kde_2d",
      "title": "A Two-dimensional Kernel Density Estimate",
      "topics": [
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        "plot.kde_2d",
        "print.kde_2d"
      ]
    },
    {
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      "title": "Find the box-cox transform exponent estimate",
      "topics": [
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        "lambda.box_cox",
        "lambda.default",
        "lambda.formula",
        "lambda.lm"
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    },
    {
      "page": "makepredictcall.normalise",
      "title": "Method function for safe prediction",
      "topics": [
        "makepredictcall.normalise"
      ]
    },
    {
      "page": "mean_c",
      "title": "Mean and variance for a circular sample",
      "topics": [
        "mean_c",
        "var_c"
      ]
    },
    {
      "page": "plot.drop_term",
      "title": "drop_term plot method",
      "topics": [
        "plot.drop_term"
      ]
    },
    {
      "page": "print.lambda",
      "title": "Print method for Box-Cox objects",
      "topics": [
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      ]
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    {
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      "title": "quine",
      "topics": [
        "quine"
      ]
    },
    {
      "page": "step_AIC",
      "title": "Stepwise model construction and inspection",
      "topics": [
        "add_term",
        "drop_term",
        "step_AIC",
        "step_BIC",
        "step_GIC"
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    {
      "page": "step_down",
      "title": "Naive backeward elimination",
      "topics": [
        "step_down"
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    },
    {
      "page": "unitChange",
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        "in2cm",
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        "unitChange"
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      "title": "An S4 class to represent alternavive complex, matrix or list input forms.",
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