Manipulate and visualize colors in a intuitive,
    low-dependency and functional way.

Prism <https://prismjs.com/> is a lightweight, extensible syntax 
    highlighter, built with modern web standards in mind. This package provides 
    server-side rendering in R using 'V8' such that no JavaScript library is
    required in the resulting HTML documents. Over 400 languages are supported.

Download, parses and tidies information from the World Prison Brief project <http://www.prisonstudies.org/>.

Enables user to perform the following:
    1. Roll 'n' number of die/dice (roll()).
    2. Toss 'n' number of coin(s) (toss()).
    3. Play the game of Rock, Paper, Scissors.
    4. Choose 'n' number of card(s) from a pack of 52 playing cards (Joker optional).

Implements two differentially private algorithms for 
  estimating L2-regularized logistic regression coefficients. A randomized
  algorithm F is epsilon-differentially private (C. Dwork, Differential
  Privacy, ICALP 2006 <DOI:10.1007/11681878_14>), if 
     |log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon
  for any pair D, D' of datasets that differ in exactly one record, any
  measurable set S, and the randomness is taken over the choices F makes.

Survey sampling using permanent random numbers (PRN's). A solution to the
    problem of unknown overlap between survey samples, which leads to a low
    precision in estimates when the survey is repeated or combined with other
    surveys. The PRN solution is to supply the U(0, 1) random numbers to the 
    sampling procedure, instead of having the sampling procedure generate them.
    In Lindblom (2014) <doi:10.2478/jos-2014-0047>, and therein cited articles,
    it is shown how this is carried out and how it improves the estimates. This
    package supports two common fixed-size sampling procedures (simple random 
    sampling and probability-proportional-to-size sampling) and includes a 
    function for transforming the PRN's in order to control the sample overlap.

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light.  This package implements the methodological framework, Point-process Response model for Optogenetics (PRO), for analyzing data from these experiments.  This method provides explicit nonlinear transformations to link the flash point-process with the spiking point-process.  Such response functions can be used to provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation.