Collection of tools to make R more convenient. Includes tools to
    summarize data using statistics not available with base R and manipulate
    objects for analyses.

R functions for "The Basics of Item Response Theory Using R" by Frank B. Baker and Seock-Ho Kim (Springer, 2017, ISBN-13: 978-3-319-54204-1) including iccplot(), icccal(), icc(), iccfit(), groupinv(), tcc(), ability(), tif(), and rasch().  For example, iccplot() plots an item characteristic curve under the two-parameter logistic model.

Provides an interface to data provided by the Bank for
  International Settlements <https://www.bis.org>, allowing for programmatic
  retrieval of a large quantity of (central) banking data.

Provides a 'ggplot2' centric approach to bivariate mapping. This is a 
    technique that maps two quantities simultaneously rather than the single value 
    that most thematic maps display. The package provides a suite of tools 
    for calculating breaks using multiple different approaches, a selection of 
    palettes appropriate for bivariate mapping and scale functions for 'ggplot2' 
    calls that adds those palettes to maps. Tools for creating bivariate legends 
    are also included.

Functions for downloading data from the Bank for
  International Settlements (BIS; <https://www.bis.org/>) in
  Basel.  Supported are only full datasets in (typically) CSV
  format.  The package is lightweight and without dependencies;
  suggested packages are used only if data is to be transformed
  into particular data structures, for instance into 'zoo'
  objects. Downloaded data can optionally be cached, to avoid
  repeated downloads of the same files.

Enables the user to infer potential synthetic lethal relationships
    by analysing relationships between bimodally distributed gene pairs in big
    gene expression datasets.  Enables the user to visualise these candidate
    synthetic lethal relationships.

A collection of functions to test spatial autocorrelation between variables, including Moran I, Geary C and Getis G together with scatter plots, functions for mapping and identifying clusters and outliers, functions associated with the moments of the previous statistics that will allow testing whether there is bivariate spatial autocorrelation, and a function that allows identifying (visualizing neighbours) on the map, the neighbors of any region once the scheme of the spatial weights matrix has been established.