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Compind (version 2.0)

Composite Indicators Functions

Description

Contains functions to enhance approaches to the Composite Indicators methods, focusing, in particular, on the normalisation and weighting-aggregation steps.

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Version

Install

install.packages('Compind')

Monthly Downloads

870

Version

2.0

License

GPL-3

Maintainer

Francesco Vidoli

Last Published

February 17th, 2018

Functions in Compind (2.0)

ci_bod_constr

Constrained Benefit of the Doubt approach (BoD)

Compind-package

Composite Indicators - Compind

EU_2020

Europe 2020 indicators

ci_geom_bod_intertemp

Intertemporal analysis for geometric mean quantity index numbers

ci_geom_gen

Generalized geometric mean quantity index numbers

normalise_ci

Normalisation and polarity functions

ci_wroclaw

Wroclaw Taxonomic Method

ci_ampi

Adjusted Mazziotta-Pareto Index (AMPI) method

ci_bod_var_w

Variance weighted Benefit of the Doubt approach (BoD variance weighted)

ci_bod_dir

Directional Benefit of the Doubt (D-BoD) model

ci_bod

Benefit of the Doubt approach (BoD)

EU_NUTS1

EU NUTS1 Transportation data

ci_factor

Weighting method based on Factor Analysis

bandwidth_CI

Multivariate mixed bandwidth selection for exogenous variables

ci_generalized_mean

Weighting method based on generalized mean

ci_rbod

Robust Benefit of the Doubt approach (RBoD)

ci_rbod_constr_bad

Robust constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators

ci_rbod_constr_bad_Q

Conditional robust constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators

ci_rbod_dir

Directional Robust Benefit of the Doubt approach (D-RBoD)

ci_bod_constr_bad

Constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators

ci_mean_min

Mean-Min Function

ci_mpi

Mazziotta-Pareto Index (MPI) method

ci_smaa_constr

Constrained stochastic multi-objective acceptability analysis (C-SMAA)

ci_rbod_spatial

Spatial robust Benefit of the Doubt approach (Sp-RBoD)