VIM: prepare – R documentation

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VIM

prepare

Transformation and standardization

Description

This function is used by the VIM GUI for transformation and standardization of the data.

Usage

prepare(
  x,
  scaling = c("none", "classical", "MCD", "robust", "onestep"),
  transformation = c("none", "minus", "reciprocal", "logarithm", "exponential",
    "boxcox", "clr", "ilr", "alr"),
  alpha = NULL,
  powers = NULL,
  start = 0,
  alrVar
)

Arguments

`x`	a vector, matrix or `data.frame`.
`scaling`	the scaling to be applied to the data. Possible values are `"none"`, `"classical"`, `MCD`, `"robust"` and `"onestep"`.
`transformation`	the transformation of the data. Possible values are `"none"`, `"minus"`, `"reciprocal"`, `"logarithm"`, `"exponential"`, `"boxcox"`, `"clr"`, `"ilr"` and `"alr"`.
`alpha`	a numeric parameter controlling the size of the subset for the MCD (if `scaling="MCD"`). See `robustbase::covMcd()`.
`powers`	a numeric vector giving the powers to be used in the Box-Cox transformation (if `transformation="boxcox"`). If `NULL`, the powers are calculated with function `car::powerTransform()`.
`start`	a constant to be added prior to Box-Cox transformation (if `transformation="boxcox"`).
`alrVar`	variable to be used as denominator in the additive logratio transformation (if `transformation="alr"`).

Details

Transformation:

"none": no transformation is used.

"logarithm": compute the the logarithm (to the base 10).

"boxcox": apply a Box-Cox transformation. Powers may be specified or calculated with the function car::powerTransform().

Standardization:

"none": no standardization is used.

"classical": apply a z-Transformation on each variable by using function scale().

"robust": apply a robustified z-Transformation by using median and MAD.

Value

Transformed and standardized data.

Author(s)

Matthias Templ, modifications by Andreas Alfons

Examples

data(sleep, package = "VIM")
x <- sleep[, c("BodyWgt", "BrainWgt")]
prepare(x, scaling = "robust", transformation = "logarithm")

VIM

Visualization and Imputation of Missing Values

v6.1.0

GPL (>= 2)

Authors

Matthias Templ [aut, cre], Alexander Kowarik [aut] (<https://orcid.org/0000-0001-8598-4130>), Andreas Alfons [aut], Gregor de Cillia [aut], Bernd Prantner [ctb], Wolfgang Rannetbauer [aut]

Initial release