Creates collapsible, expandable 'HTML' tables from hierarchical
    data. Supports data frame input with multi-level grouping, custom column
    formatters, bottom-up rollup aggregation, and CSS-variable-based theming.
    Works in 'Shiny' applications, R Markdown, 'Quarto', and the 'RStudio' Viewer.

Computes effective population size (Ne) and the Ne/N ratio for
    stage-structured populations using the matrix population model framework
    of Yonezawa (2000) <doi:10.1111/j.0014-3820.2000.tb01244.x>. Functions
    are provided for sexually reproducing, clonally reproducing, and mixed
    (sexual + clonal) populations. Includes sensitivity and elasticity
    analyses for Ne/N with respect to vital rates.

Clinical reporting figures require to use consistent colors
    and configurations. As a part of the Roche open-source clinical
    reporting project, namely the NEST project, the 'nestcolor' package
    specifies the color code and default theme with specifying 'ggplot2'
    theme parameters. Users can easily customize color and theme settings
    before using the reset of NEST packages to ensure consistent settings
    in both static and interactive output at the downstream.

Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.

Provides functions for specifying and fitting nested
    dichotomy logistic regression models for a multi-category response and
    methods for summarising and plotting those models.  Nested dichotomies are
    statistically independent, and hence provide an additive decomposition
    of tests for the overall 'polytomous' response.  When the dichotomies
    make sense substantively, this method can be a simpler alternative to
    the standard 'multinomial' logistic model which compares response
    categories to a reference level.  See: J. Fox (2016), "Applied
    Regression Analysis and Generalized Linear Models", 3rd Ed., ISBN
    1452205663.