Package: Compind 3.1

Compind: Composite Indicators Functions

A collection of functions to calculate Composite Indicators methods, focusing, in particular, on the normalisation and weighting-aggregation steps, as described in OECD Handbook on constructing composite indicators: methodology and user guide <https://www.oecd-ilibrary.org/economics/handbook-on-constructing-composite-indicators-methodology-and-user-guide_9789264043466-en>, 'Vidoli' and 'Fusco' and 'Mazziotta' <doi:10.1007/s11205-014-0710-y>, 'Mazziotta' and 'Pareto' (2016) <doi:10.1007/s11205-015-0998-2>, 'Van Puyenbroeck and 'Rogge' <doi:10.1016/j.ejor.2016.07.038> and other authors.

Authors:Francesco Vidoli, Elisa Fusco

Compind_3.1.tar.gz
Compind_3.1.zip(r-4.5)Compind_3.1.zip(r-4.4)Compind_3.1.zip(r-4.3)
Compind_3.1.tgz(r-4.4-any)Compind_3.1.tgz(r-4.3-any)
Compind_3.1.tar.gz(r-4.5-noble)Compind_3.1.tar.gz(r-4.4-noble)
Compind_3.1.tgz(r-4.4-emscripten)Compind_3.1.tgz(r-4.3-emscripten)
Compind.pdf |Compind.html✨
Compind/json (API)
NEWS

# Install 'Compind' in R:

install.packages('Compind', repos = c('https://fvidoli.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

BLI_2017 - Better Life Index 2017 indicators
EU_2020 - Europe 2020 indicators
EU_NUTS1 - EU NUTS1 Transportation data
data_HPI - Happy Planet Index 2017-2019 indicators

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.20 score 40 scripts 432 downloads 26 exports 159 dependencies

Last updated 8 months agofrom:952c099ff0. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 22 2024
R-4.5-win	OK	Oct 22 2024
R-4.5-linux	OK	Oct 22 2024
R-4.4-win	OK	Oct 22 2024
R-4.4-mac	OK	Oct 22 2024
R-4.3-win	OK	Oct 22 2024
R-4.3-mac	OK	Oct 22 2024

Exports:bandwidth_CI ci_ampi ci_bod ci_bod_constr ci_bod_constr_bad ci_bod_dir ci_bod_mdir ci_bod_var_w ci_factor ci_factor_mixed ci_generalized_mean ci_geom_bod_intertemp ci_geom_gen ci_mean_min ci_mpi ci_ogwa ci_owa ci_rbod ci_rbod_constr_bad ci_rbod_constr_bad_Q ci_rbod_dir ci_rbod_mdir ci_rbod_spatial ci_smaa_constr ci_wroclaw normalise_ci

Dependencies:abind backports base64enc Benchmarking boot broom bslib cachem car carData checkmate class classInt cli cluster coda codetools colorspace cowplot cpp11 crosstalk cubature data.table DBI deldir DEoptimR Deriv digest doBy dplyr DT e1071 ellipse emmeans estimability evaluate expm FactoMineR fansi farver fastmap flashClust FNN fontawesome foreign Formula fs generics geometry ggplot2 ggrepel glue GPArotation gridExtra gtable GWmodel highr Hmisc htmlTable htmltools htmlwidgets httpuv intervals isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval leaps LearnBayes lifecycle linprog lme4 lpSolve lpSolveAPI magic magrittr MASS Matrix MatrixModels mcmc MCMCpack memoise mgcv microbenchmark mime minqa mnormt modelr multcomp multcompView munsell mvtnorm nlme nloptr nnet nonparaeff np numDeriv pbkrtest pillar pkgconfig popdemo promises proxy psych purrr quadprog quantreg R6 rappdirs RColorBrewer Rcompadre Rcpp RcppArmadillo RcppEigen RcppProgress rlang rmarkdown robustbase rpart rstudioapi s2 sandwich sass scales scatterplot3d sf smaa sp spacetime SparseM spatialreg spData spdep stringi stringr survival TH.data tibble tidyr tidyselect tinytex ucminf units utf8 vctrs viridis viridisLite withr wk xfun xts yaml zoo

Compind: Composite indicators functions based on frontiers in R

Rendered fromCompind_vignette.pdf.asisusingR.rsp::asison Oct 22 2024.

Last update: 2017-06-20
Started: 2016-06-27

Citation

Readme and manuals

Help Manual

Help page	Topics
Composite Indicators - Compind	Compind-package
Multivariate mixed bandwidth selection for exogenous variables	bandwidth_CI
Better Life Index 2017 indicators	BLI_2017
Adjusted Mazziotta-Pareto Index (AMPI) method	ci_ampi
Benefit of the Doubt approach (BoD)	ci_bod
Constrained Benefit of the Doubt approach (BoD)	ci_bod_constr
Constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators	ci_bod_constr_bad
Directional Benefit of the Doubt (D-BoD) model	ci_bod_dir
Multi-directional Benefit of the Doubt approach (MDBoD)	ci_bod_mdir
Variance weighted Benefit of the Doubt approach (BoD variance weighted)	ci_bod_var_w
Weighting method based on Factor Analysis	ci_factor
Weighting method based on Factor analysis of mixed data (FAMD)	ci_factor_mixed
Weighting method based on generalized mean	ci_generalized_mean
Intertemporal analysis for geometric mean quantity index numbers	ci_geom_bod_intertemp
Generalized geometric mean quantity index numbers	ci_geom_gen
Mean-Min Function	ci_mean_min
Mazziotta-Pareto Index (MPI) method	ci_mpi
Ordered Geographically Weighted Average (OWA)	ci_ogwa
Ordered Weighted Average (OWA)	ci_owa
Robust Benefit of the Doubt approach (RBoD)	ci_rbod
Robust constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators	ci_rbod_constr_bad
Conditional robust constrained Benefit of the Doubt approach (BoD) in presence of undesirable indicators	ci_rbod_constr_bad_Q
Directional Robust Benefit of the Doubt approach (D-RBoD)	ci_rbod_dir
Robust multi-directional Benefit of the Doubt approach (MDRBoD)	ci_rbod_mdir
Spatial robust Benefit of the Doubt approach (Sp-RBoD)	ci_rbod_spatial
Constrained stochastic multi-objective acceptability analysis (C-SMAA)	ci_smaa_constr
Wroclaw Taxonomic Method	ci_wroclaw
Happy Planet Index 2017-2019 indicators	data_HPI
Europe 2020 indicators	EU_2020
EU NUTS1 Transportation data	EU_NUTS1
Normalisation and polarity functions	normalise_ci