Provides estimations of the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) based on the two-stages mixed-subjects ROC curve estimator (Diaz-Coto et al. (2020) <doi:10.1515/ijb-2019-0097> and Diaz-Coto et al. (2020) <doi:10.1080/00949655.2020.1736071>).

Datasets used in "Statistical Methods for the Social Sciences"
    (SMSS) by Alan Agresti and Barbara Finlay.

Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.

Implementation of the SMuRF algorithm of Devriendt et al. (2021) <doi:10.1016/j.insmatheco.2020.11.010> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.

Testing the mediation effect of multiple SNPs on an outcome through a mediator.

Implementation of the structural model for variances in order to
        detect differentially expressed genes from gene expression data.

Mosaic diagram, scatterplot matrix, Andrews curves, parallel coordinate diagram, radar diagram, 
   and Chernoff plots as a Shiny app, which allow the order of variables to be changed interactively. 
   The apps are intended as teaching examples.

Simple implementation of Semantic Versioning 2.0.0 ('SemVer') on the
    'vctrs' package.  This package provides a simple way to create,
    compare, and manipulate semantic versions in R. It is designed to be
    lightweight and easy to use.

Build and manipulate probability distributions of the skew-normal 
  family and some related ones, notably the skew-t and the SUN families. 
  For the skew-normal and the skew-t distributions, statistical methods are 
  provided for data fitting and model diagnostics, in the univariate and the 
  multivariate case.

A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.