MAD: Mean absolute difference of rank

In Indicator: Composite 'Indicator' Construction and Imputation Data

Mean absolute difference of rank

Description

Function to calculate the mean absolute difference of rank for different methods

Usage

MAD(matrix_data)

Arguments

matrix_data

data matrix of indicator

Details

Function to calculate the mean absolute difference of rank for different methods. Create the matrix of ranking for different columns, the rank is the high value is the first. Calculate the different in absolute values for different columns and calculate the mean for different methods

Value

It returns a data frame of mean absolute difference of rank for different methods

References

Matteo Mazziotta & Adriano Pareto, 2018. "Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 967-976, April

Examples

data("Education")
Indicator_MPI=linear_aggregation_MPI(Education)
Indicator_AMPI=linear_aggregation_AMPI(Education)
Indicator_GA=geometric_aggregation(Education)
All_Indicator=cbind(Indicator_MPI,Indicator_AMPI,Indicator_GA)
MAD=MAD(All_Indicator)
print(MAD)

Indicator documentation built on April 4, 2025, 4:35 a.m.