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 FLEX method, developed by Yoon and Choi (2013) <doi:10.1007/978-3-642-33042-1_21>, performs least squares estimation for fuzzy predictors and outcomes, generating crisp regression coefficients by minimizing the distance between observed and predicted outcomes. It also provides functions for fuzzifying data and inference tasks, including significance testing, fit indices, and confidence interval estimation.

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.

Allows maximum likelihood fitting of cluster-weighted models, a class of mixtures of regression models with random covariates. 
            Methods are described in Angelo Mazza, Antonio Punzo, Salvatore Ingrassia (2018) <doi:10.18637/jss.v086.i02>.

Format for converting an R Markdown document to a grid
    oriented dashboard. The dashboard flexibly adapts the size of it's
    components to the containing web page.

Provides tools to work with the Flexible Dirichlet
    distribution. The main features are an E-M algorithm for computing the maximum
    likelihood estimate of the parameter vector and a function based on conditional
    bootstrap to estimate its asymptotic variance-covariance matrix. It contains
    also functions to plot graphs, to generate random observations and to handle
    compositional data.