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VIM (version 3.0.2)

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
alpha
a numeric parameter controlling the size of the subset for the MCD (if scaling="MCD"). See 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 box.cox.powers<
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").

Value

  • Transformed and standardized data.

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 box.cox.powers. 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.

See Also

scale, box.cox.powers

Examples

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

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