normalise: Normalise the Vairables

In jkapila/vcvn: Variable Selection, Curve Fitting, Variable Conversion and Normalisation

Description

Normalise the Vairables

Usage

normalise(x, y = NULL, method = "zscore", na.rm = TRUE, diff.val = 0,
  norm.list = list(), depedentMod = NULL, scores = NULL)

Arguments

x	A vector or Data frame to be normalised
y	A depedent vector for depedent normalisation. Default value is NULL(indepedent normalisation).
method	A method or a vector of methods to apply normalisation on varaibles. If vector not equal to num of variables "unit" normalisation is implemented for the rest. Methods implemented are 1) unitMean 2) unitSD 3) unitMeanSD 4) minMax 5) boxCox 6) log 7) meanDiff 8) medianDiff 9) meanSDDiff 10) medianSDDiff 11) zscore (zero Mean and unit SD) 12) power
na.rm	A boolean for na treatment. Default is TRUE.
diff.val	Difference required from mean and median
norm.list	a list of vlaues for flexible normalisation
depedentMod	Model to be used for Dependent Normalisation(lm or glm)
scores	scores to be used for evaluting the normalisation

Details

log is impleted with 1 added to the value

Value

Normalised vector or a data frame

Examples

normalise(mtcars)

jkapila/vcvn documentation built on May 19, 2019, 4:05 p.m.