Simplifies the process of creating essential visualizations
    in R, offering a range of plotting functions for common chart types
    like violin plots, pie charts, and histograms.  With an intuitive
    interface, users can effortlessly customize colors, labels, and
    styles, making it an ideal tool for both beginners and experienced
    data analysts. Whether exploring datasets or producing quick visual
    summaries, this package provides a streamlined solution for
    fundamental graphics in R.

This is a set of functions to retrieve information about GIMMS
    NDVI3g files currently available online; download (and re-arrange, in the 
    case of NDVI3g.v0) the half-monthly data sets; import downloaded files from 
    ENVI binary (NDVI3g.v0) or NetCDF format (NDVI3g.v1) directly into R based 
    on the widespread 'raster' package; conduct quality control; and generate 
    monthly composites (e.g., maximum values) from the half-monthly input data. 
    As a special gimmick, a method is included to conveniently apply the 
    Mann-Kendall trend test upon 'Raster*' images, optionally featuring 
    trend-free pre-whitening to account for lag-1 autocorrelation.

Implements GINA-X, a genome-wide iterative fine-mapping method designed for non-Gaussian traits. It supports the identification of credible sets of genetic variants.

Providing various equations to calculate Gini coefficients.
    The methods used in this package can be referenced from Brown MC (1994) <doi: 10.1016/0277-9536(94)90189-9>.

An implementation of Gini-based weighting approaches in constructing composite indicators, providing functionalities for normalization, aggregation, and ranking comparison.

Estimation of the effect of each income source on income inequalities based on the decomposition of Lerman and Yitzhaki (1985) <doi:10.2307/1928447>.

An implementation of a new Gini covariance and correlation to measure dependence between a categorical and numerical variables. Dang, X., Nguyen, D., Chen, Y. and Zhang, J., (2018) <arXiv:1809.09793>.