This package is considered a duplicate. The official version of this package is found at:https://gianmarcoborrata.r-universe.dev/Indicator

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.tar.gz(r-4.5-noble)Indicator_0.1.3.tar.gz(r-4.4-noble)
Indicator_0.1.3.tgz(r-4.4-emscripten)Indicator_0.1.3.tgz(r-4.3-emscripten)
Indicator.pdf |Indicator.html✨
Indicator/json (API)
NEWS

# Install 'Indicator' in R:

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

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

Datasets:

Education - Education

2.18 score 491 downloads 21 exports 101 dependencies

Last updated 29 days agofrom:f4a23ed92a. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Nov 28 2024
R-4.5-linux	OK	Nov 28 2024

Exports:columns_with_nan compute_CI geometric_aggregation get_all_performance get_all_performance_boot Jevons_aggregation linear_aggregation linear_aggregation_AMPI linear_aggregation_MPI lm_imputation MAD min_max min_max_GM normalization_abov_below_mean pca_weighting performance_nan_imputation rank_aggregation rank_normalisation standardization Standardization_AMPI standardization_MPI

Dependencies:abind backports base64enc boot broom bslib cachem car carData cli cluster colorspace cowplot cpp11 crosstalk Deriv digest doBy dplyr DT ellipse emmeans estimability evaluate FactoMineR fansi farver fastmap flashClust fontawesome Formula fs generics ggplot2 ggrepel glue gtable highr htmltools htmlwidgets httpuv isoband jquerylib jsonlite knitr labeling later lattice lazyeval leaps lifecycle lme4 magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa missMethods modelr multcompView munsell mvtnorm nlme nloptr nnet norm numDeriv pbkrtest pillar pkgconfig promises purrr quantreg R6 rappdirs RColorBrewer Rcpp RcppEigen rlang rmarkdown sass scales scatterplot3d SparseM stringi stringr survival tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Indicator: A package for constructing composite indicators, imputing and evaluating missing data imputation	Indicator-package Indicator
Function to get the names of the columns with NAN values	columns_with_nan
Calculation of Condition Indices	compute_CI
Education	Education
Geometric Aggregation	geometric_aggregation
Function to evaluate different nan imputation methods	get_all_performance
Function to evaluate different nan imputation methods with bootstrap	get_all_performance_boot
Jevons static aggregation	Jevons_aggregation
Linear Aggregation	linear_aggregation
Adjusted Mazziotta-Pareto index	linear_aggregation_AMPI
Mazziotta-Pareto index	linear_aggregation_MPI
Function to apply nan inputation with linear regression	lm_imputation
Mean absolute difference of rank	MAD
Min-max normalization	min_max
Normalization for the Geometric Mean	min_max_GM
Normalization above or below the mean	normalization_abov_below_mean
Function that weight the quantitative variable by PCA method	pca_weighting
Function to evaluate nan imputation method's performance	performance_nan_imputation
Ranking Aggregation	rank_aggregation
Rank normalization	rank_normalisation
Standardization	standardization
Standardization of data with Adjusted Maziotta-Pareto index	Standardization_AMPI
Standardization of data with Maziotta-Pareto index	standardization_MPI

Package: Indicator 0.1.3

Indicator: Composite 'Indicator' Construction and Imputation Data

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