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.

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.

Estimates cumulative history for time-series for continuously
    viewed bistable perceptual rivalry displays. Computes cumulative history
    via a homogeneous first order differential process. I.e., it assumes
    exponential growth/decay of the history as a function time and perceptually
    dominant state, Pastukhov & Braun (2011) <doi:10.1167/11.10.12>.
    Supports Gamma, log normal, and normal distribution families.
    Provides a method to compute history directly and example of using the
    computation on a custom Stan code.