Extensions to 'ggplot2' respecting the grammar of graphics
    paradigm. Statistics: locate and tag peaks and valleys; label plot with the
    equation of a fitted polynomial or other types of models including major
    axis, quantile and robust and resistant regression. Labels for P-value, 
    R^2 or adjusted R^2 or information criteria for fitted models; parametric
    and non-parametric correlation; label with ANOVA table for fitted models; 
    label with summary table for fitted models; annotations for multiple 
    comparisons with adjusted P-values. Model fit classes for which suitable 
    methods are provided by package 'broom' and 'broom.mixed' are supported as 
    well as user-defined wrappers on model fit functions. Scales and stats to 
    build volcano and quadrant plots based on
    outcomes, fold changes, p-values and false discovery rates.

At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling
  activities in order to reduce the overall effort required for generating such plots.
  For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox,
  called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient
  for publication and submissions using few lines of code. This package focuses on plots recommended by ISoP
  <doi:10.1002/psp4.12161>. While not required, you can get/install the 'R' 'lixoftConnectors'
    package in the 'Monolix' installation, as described at the following url
    <https://monolixsuite.slp-software.com/r-functions/2024R1/installation-and-initialization>.
    When 'lixoftConnectors' is available, 'R' can use 'Monolix' directly to create the required
    Chart Data instead of exporting it from the 'Monolix' gui.

A cross between a 2D density plot and a scatter plot,
    implemented as a 'ggplot2' geom. Points in the scatter plot are 
    colored by the number of neighboring points. This is useful to
    visualize the 2D-distribution of points in case of overplotting.