Indicator (version 0.1.3)

normalization_abov_below_mean: Normalization above or below the mean

Description

This transformation considers the indicators which are above and below an arbitrarily defined threshold, p, around the mean. The threshold p builds a neutral region around the mean, where the transformed indicator is zero. This reduces the sharp discontinuity, from -1 to +1, which exists across the mean value to two minor discontinuities, from -1 to 0 and from 0 to +1, across the thresholds

Usage

normalization_abov_below_mean(data, p = 0.01)

Value

It returns a datafame of normalized data

Arguments

data

dataframe with rows = observations and columns = quantiative variables

p

threshold for the window

Details

This function to normalize in -1, 0, and 1

References

OECD/European Union/EC-JRC (2008), Handbook on Constructing Composite Indicators: Methodology and User Guide, OECD Publishing, Paris, <https://doi.org/10.1787/9789264043466-en>

Examples

data("Education")
Indicator=normalization_abov_below_mean(Education)
print(Indicator)

#---With different threshold
Indicator=normalization_abov_below_mean(Education,p=0.1)
print(Indicator)