Adds a 'tintshade' aesthetic to 'ggplot2' that varies the
    lightness of a mapped 'colour' or 'fill' within each hue group, keeping
    the plotted layer and its legend in sync. Supports both nested designs
    (each item belongs to one hue) and crossed designs (each lightness level
    appears across hues).

Provides 'ggplot2' geoms that allow groups of data points to be
    outlined or highlighted for emphasis. This is particularly useful when
    working with dense datasets that are prone to overplotting.

Provides a simple way to translate text elements in 'ggplot2' plots using a dictionary-based approach.

Provides 'ggplot2' geoms analogous to 'geom_col()' and 'geom_bar()'
    that allow for treemaps using 'treemapify' nested within each bar segment.
    Also provides geometries for subgroup bordering and text annotation.

Add trendline and confidence interval of linear or nonlinear regression model and
    show equation to 'ggplot' as simple as possible. For a general overview of the methods used in
	  this package, see Ritz and Streibig (2008) <doi:10.1007/978-0-387-09616-2> and 
	  Greenwell and Schubert Kabban (2014) <doi:10.32614/RJ-2014-009>.

A collection of several geoms to create graphics, using
    'ggplot2' and the Cartesian coordinate system. You use the familiar
    mapping 'Grammar of Graphics' without the need to do another
    transformation into polar coordinates.

Provides dual-stroke and contrast-aware extensions to
    'ggplot2', designed for improved visibility and accessibility in
    complex visualizations. Includes geoms for dual-stroke segments,
    regression lines, curved annotations, function plots, paths, and
    adaptive text. Also includes utility functions for computing
    contrast-aware color pairs and perceptually distinct highlight
    palettes using Web Content Accessibility Guidelines (WCAG)-based 
    contrast logic.

An implementation of the generalized graded unfolding model (GGUM) in R, see Roberts, Donoghue, and Laughlin (2000) <doi:10.1177/01466216000241001>). It allows to simulate data sets based on the GGUM. It fits the GGUM and the GUM, and it retrieves item and person parameter estimates. Several plotting functions are available (item and test information functions; item and test characteristic curves; item category response curves). Additionally, there are some functions that facilitate the communication between R and 'GGUM2004'. Finally, a model-fit checking utility, MODFIT(), is also available.