Produces an Odds Ratio (OR) Plot to visualise the result of a 
    logistic regression analysis.
    Provide it with a binomial regression model produced by 'glm()' and it will 
    convert the estimates to odds ratios with a 95% confidence interval and 
    plot the results using 'ggplot2'.

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.

Figures rendered on graphics devices are usually 
 rescaled to fit pre-determined device dimensions. 'plotscale' 
 implements the reverse: desired plot dimensions are specified 
 and device dimensions are calculated to accommodate marginal
 material, giving consistent proportions for plot elements.
 Default methods support grid graphics such as lattice and ggplot.
 See "example('devsize')" and "vignette('plotscale')".

A framework for creating interactive figures for data exploration. 
    All plots are automatically linked and support several kinds of interactive features,
    including selection, zooming, panning, and parameter manipulation. The figures
    can be interacted with either manually, using a mouse and a keyboard, 
    or by running code from inside an active R session.

Contains a graphical user interface to generate the diagnostic
    plots proposed by Bauer (2005; <doi:10.1207/s15328007sem1204_1>), 
    Pek & Chalmers (2015; <doi:10.1080/10705511.2014.937790>), and
    Pek, Chalmers, R. Kok, & Losardo (2015; <doi:10.3102/1076998615589129>) to investigate
    nonlinear bivariate relationships in latent regression models using structural
    equation mixture models (SEMMs).