Convenience functions for smooth conversion from 'ggplot' to 'plotly' where the conversion using ggplotly() usually gives an unexpected labels. The package ease the process of making a 'plotly' figures generated from 'ggplot2' object more aesthetic in terms of labels and customizability.

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; labels
    with P-value, R^2 or adjusted R^2 or information criteria for fitted models;
    label with ANOVA table for fitted models; label with summary for fitted
    models. Model fit classes for which suitable methods are provided by package
    'broom' and 'broom.mixed' are supported. 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://monolix.lixoft.com/monolix-api/lixoftconnectors_installation/>.
    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.