| Type: | Package |
| Version: | 1.0.0 |
| Title: | Composite Index Builder & Analytics 'shiny' App |
| Description: | Provides an interactive 'shiny' web application for constructing, analyzing, and visualizing composite indices from multidimensional datasets. Users can upload or select indicator data, group variables into logical categories, apply normalization and weighting methods (such as 'equal' or 'custom' schemes), and compute aggregate composite indices. The 'shiny' interface includes tools for exploring results through tables, plots, and data exports, making it useful for researchers, policymakers, and analysts interested in index-based evaluations. |
| License: | GPL-3 |
| Depends: | R (≥ 4.1.0) |
| Imports: | shiny, plotly, shinydashboard, dplyr, readxl, forecast, tidyr, corrplot, missForest, zoo, tibble, DT, ggplot2, networkD3, psych |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Maintainer: | Leila Marvian Mashhad <Leila.marveian@gmail.com> |
| NeedsCompilation: | no |
| Encoding: | UTF-8 |
| Packaged: | 2025-10-14 19:22:03 UTC; HAMIAN |
| Author: | Hossein Hassani [aut], Leila Marvian Mashhad [aut, cre], Steve Macfeely [aut], Petra Kynclova [aut], Nour Barnat [aut], Fernando CANTU BAZALDUA [aut] |
| Repository: | CRAN |
| Date/Publication: | 2025-10-20 19:20:02 UTC |
Composite Index Builder Shiny Application
Description
The 'compIndexBuilder' package provides a Shiny application and helper functions to build composite indices from tabular indicator data.
Details
This package includes modules for data preparation, weighting and
visualization. The Shiny interface is intended to be launched via
compIndexBuilder in an interactive R session.
Value
No return value, called for side effects. The function launches a 'Shiny' web application for composite index construction.
Author(s)
Hossein Hassani and Leila Marvian Mashhad and Steve Macfeely and Petra Kynclova and Nour Barnat and Fernando CANTU BAZALDUA.
See Also
Examples
if (interactive()) {
toy_data <- data.frame(a = 1:5, b = 2:6)
res <- compIndexBuilder(toy_data)
summary(res)
}