Create the density contour plot for bivariate inverse Gaussian distribution for given non negative random variables.

The 'plotcli' package provides terminal-based plotting in R.
             It supports colored scatter plots, line plots, bar plots, and box plots. The package allows users 
             to customize plot appearance, add titles, labels, ticks, and legends, and output the plot as a text-based visualization.

This function plots a contour line with a user-defined probability and tightness of fit.

Easily visualize and animate 'tabledap' and 'griddap' objects obtained via the 'rerddap' package in a simple one-line command,  using either base graphics or 'ggplot2' graphics. 'plotdap' handles extracting and reshaping the data,  map projections and continental outlines.  Optionally the data can be animated through time using the 'gganmiate' package.

Provides a ggplot2 front end to plot summary statistics on danish provinces,
    regions, municipalities, and zipcodes. The needed geoms of each of the four levels are 
    inherent in the package, thus making these types of plots easy for the user. This is essentially 
    an updated port of the previously available 'mapDK' package by Sebastian Barfort.

When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions. Note: Most of the functions were part of the package 'itsadug', which is now split in two packages: 1. the package 'itsadug', which contains the core functions for visualizing and evaluating nonlinear regression models, and 2. the package 'plotfunctions', which contains more general plot functions.