Package: Indicator 0.1.3

Gianmarco Borrata

Indicator: Composite 'Indicator' Construction and Imputation Data

Different functions includes constructing composite indicators, imputing missing data, and evaluating imputation techniques. Additionally, different tools for data normalization. Detailed methodologies of 'Indicator' package are: OECD/European Union/EC-JRC (2008), "Handbook on Constructing Composite Indicators: Methodology and User Guide", OECD Publishing, Paris, <doi:10.1787/533411815016>, Matteo Mazziotta & Adriano Pareto, (2018) "Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices" <doi:10.1007/s11205-017-1577-5> and De Muro P., Mazziotta M., Pareto A. (2011), "Composite Indices of Development and Poverty: An Application to MDGs" <doi:10.1007/s11205-010-9727-z>.

Authors:Gianmarco Borrata [aut, cre], Pasquale Pipiciello [aut]

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Indicator/json (API)
NEWS

# Install 'Indicator' in R:
install.packages('Indicator', repos = c('https://gianmarcoborrata.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gianmarcoborrata/indicator/issues

Datasets:

On CRAN:

Conda:

3.00 score 1 stars 1 scripts 165 downloads 21 exports 104 dependencies

Last updated 4 months agofrom:bf5e544827. Checks:4 OK, 4 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-winOKMar 27 2025
R-4.5-macOKMar 27 2025
R-4.5-linuxOKMar 27 2025
R-4.4-winNOTEMar 27 2025
R-4.4-macNOTEMar 27 2025
R-4.3-winNOTEMar 27 2025
R-4.3-macNOTEMar 27 2025

Exports:columns_with_nancompute_CIgeometric_aggregationget_all_performanceget_all_performance_bootJevons_aggregationlinear_aggregationlinear_aggregation_AMPIlinear_aggregation_MPIlm_imputationMADmin_maxmin_max_GMnormalization_abov_below_meanpca_weightingperformance_nan_imputationrank_aggregationrank_normalisationstandardizationStandardization_AMPIstandardization_MPI

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecowplotcpp11crosstalkDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeFormulafsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamissMethodsmodelrmultcompViewmunsellmvtnormnlmenloptrnnetnormnumDerivpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrmarkdownsassscalesscatterplot3dSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml