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]

Indicator_0.1.3.tar.gz
Indicator_0.1.3.zip(r-4.7-any)Indicator_0.1.3.zip(r-4.6-any)Indicator_0.1.3.zip(r-4.5-any)
Indicator_0.1.3.tgz(r-4.6-any)Indicator_0.1.3.tgz(r-4.5-any)
Indicator_0.1.3.tar.gz(r-4.7-any)Indicator_0.1.3.tar.gz(r-4.6-any)
Indicator_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Indicator/json (API)

# 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:

2.70 score 1 stars 3 scripts 288 downloads 21 exports 113 dependencies

Last updated from:bf5e544827. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK203
source / vignettesOK218
linux-releaseOK216
macos-releaseOK224
macos-oldrelOK211
windows-develOK149
windows-releaseOK123
windows-oldrelOK121
wasm-releaseOK232

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:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecowplotcpp11crosstalkDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetsirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamissMethodsmodelrmultcompViewmvtnormnlmenloptrnnetnormnumDerivotelpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownS7sassscalesscatterplot3dshowtextshowtextdbSparseMstringistringrsurvivalsysfontstibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisLitewithrxfunyamlzoo