Provides functions for creating flashcard decks of terms and 
    definitions. This package creates HTML slides using 'revealjs' that can be 
    viewed in the 'RStudio' viewer or a web browser.  Users can create 
    flashcards from either existing built-in decks or create their own from CSV
    files or vectors of function names.

Contingency Tables are a pain to work with when you want to run regressions.
  This package takes them, flattens them into a long data frame, so you can more easily analyse them!
  As well, you can calculate other related statistics. All of this is done so in a 'tidy' manner,
  so it should tie in nicely with 'tidyverse' series of packages.

Transformations that allow obtaining a flat table from
    reports in text or Excel format that contain data in the form of pivot
    tables. They can be defined for a single report and applied to a set
    of reports.

On import, the XML information is converted to a dataframe that reflects the hierarchical XML structure. Intuitive functions allow to navigate within this transparent XML data structure (without any knowledge of 'XPath'). 'flatXML' also provides tools to extract data from the XML into a flat dataframe that can be used to perform statistical operations. It also supports converting dataframes to XML.

Streamlines the process of updating changelogs (NEWS.md)
    and versioning R packages developed in git repositories.

Perform variable selection in settings with possibly missing data
    based on extrinsic (algorithm-specific) and intrinsic (population-level)
    variable importance. Uses a Super Learner ensemble to estimate the
    underlying prediction functions that give rise to estimates of variable importance. For more information about the methods, please see Williamson and Huang (2023+) <arXiv:2202.12989>.

The main function kcca implements a general framework for
  k-centroids cluster analysis supporting arbitrary distance measures
  and centroid computation. Further cluster methods include hard
  competitive learning, neural gas, and QT clustering. There are
  numerous visualization methods for cluster results (neighborhood
  graphs, convex cluster hulls, barcharts of centroids, ...), and
  bootstrap methods for the analysis of cluster stability.