Plot model surfaces for a wide variety of models
        using partial dependence plots and other techniques.
        Also plot model residuals and other information on the model.

Graphical methods testing multivariate normality assumption. Methods including assessing score function, and moment generating functions,independent transformations and linear transformations. For more details see Tran (2024),"Contributions to Multivariate Data Science: Assessment and Identification of Multivariate Distributions and Supervised Learning for Groups of Objects." , PhD thesis,
  <https://our.oakland.edu/items/c8942577-2562-4d2f-8677-cb8ec0bf6234>.

Produces odds ratio analyses with comprehensive reporting tools. Generates 
    plots, summary tables, and diagnostic checks for logistic regression models 
    fitted with 'glm()' using binomial family. Provides visualisation methods, 
    formatted reporting tables via 'gt', and tools to assess logistic regression 
    model assumptions.

Plot principal component histograms around a bivariate
        scatter plot.

Useful set of tools for plotting network diagrams in any kind of project.

Lots of plots, various labeling, axis and color scaling functions. The author/maintainer died in September 2023.

Most ROC curve plots obscure the cutoff values and inhibit
    interpretation and comparison of multiple curves. This attempts to address
    those shortcomings by providing plotting and interactive tools. Functions
    are provided to generate an interactive ROC curve plot for web use, and
    print versions. A Shiny application implementing the functions is also
    included.

Provides tools for visual exploratory data analysis with nested
    data. Includes functions for creating bivariate plots, dot plots,
    histograms, and violin plots for each group or unit in nested data.
    Methods are described in Crabtree and Nelson (2017) "Plotrr: Functions for
    making visual exploratory data analysis with nested data easier"
    <doi:10.21105/joss.00190>.