An 'SCSS' compiler, powered by the 'LibSass' library. With this,
    R developers can use variables, inheritance, and functions to generate
    dynamic style sheets. The package uses the 'Sass CSS' extension language,
    which is stable, powerful, and CSS compatible.

A meta-package that aims to make 'R' easier for everyone, 
    especially programmers who have a background in 'SAS®' software.
    This set of packages brings many useful concepts to 'R', including
    data libraries, data dictionaries, formats 
    and format catalogs, a data step, and a traceable log.  The 'flagship'
    package is a reporting package that can output in text, rich text, 'PDF', 
    'HTML', and 'DOCX' file formats.

Tools for analyzing tail dependence in any sample or in particular theoretical models.  The package uses only theoretical and non parametric methods, without inference.  The primary goals of the package are to provide: (a)symmetric multivariate extreme value models in any dimension;  theoretical and empirical indices to order tail dependence;  theoretical and empirical graphical methods to visualize tail dependence.

Bundles functions used to analyze the harmfulness of trial errors in criminal trials.
    Functions in the Scientific Analysis of Trial Errors ('SATE') package help users estimate the 
    probability that a jury will find a defendant guilty given jurors' preferences for a guilty 
    verdict and the uncertainty of that estimate. Users can also compare actual and hypothetical 
    trial conditions to conduct harmful error analysis. The relationship between individual jurors' 
    verdict preferences and the probability that a jury returns a guilty verdict has been studied 
    by Davis (1973) <doi:10.1037/h0033951>; MacCoun & Kerr (1988) <doi:10.1037/0022-3514.54.1.21>, 
    and Devine et el. (2001) <doi:10.1037/1076-8971.7.3.622>, among others.

Herein, we provide a broad variety of functions which are useful
    for handling, manipulating, and visualizing satellite-based remote sensing 
    data. These operations range from mere data import and layer handling (eg 
    subsetting), over Raster* typical data wrangling (eg crop, extend), to more 
    sophisticated (pre-)processing tasks typically applied to satellite imagery 
    (eg atmospheric and topographic correction). This functionality is 
    complemented by a full access to the satellite layers' metadata at any 
    stage and the documentation of performed actions in a separate log file. 
    Currently available sensors include Landsat 4-5 (TM), 7 (ETM+), and 8 
    (OLI/TIRS Combined), and additional compatibility is ensured for the Landsat 
    Global Land Survey data set.