Population genetic data such as 'Single Nucleotide
        Polymorphisms' (SNPs) is often used to identify genomic regions
        that have been under recent natural or artificial selection
        and might provide clues about the molecular mechanisms of adaptation. 
        One approach, the concept of an 'Extended Haplotype Homozygosity' (EHH), 
        introduced by (Sabeti 2002) <doi:10.1038/nature01140>, has given rise to 
        several statistics designed for whole genome scans. 
        The package provides functions to compute three of these,
        namely: 'iHS' (Voight 2006) <doi:10.1371/journal.pbio.0040072> for
        detecting positive or 'Darwinian' selection within a single population as well as
        'Rsb' (Tang 2007) <doi:10.1371/journal.pbio.0050171> and 
        'XP-EHH' (Sabeti 2007) <doi:10.1038/nature06250>, targeted
        at differential selection between two populations. 
        Various plotting functions are included to facilitate
        visualization and interpretation of these statistics.

Contains example data for the 'rehh' package.

Facilitates replication of Twitter-based research by handling
    common programming tasks needed when downloading tweets.  Specifically, it ensures a 
    user does not exceed Twitter’s rate limits, and it saves tweets in moderately sized files.  
    While a user could perform these tasks in their own code, doing so may be beyond the 
    capabilities of many users.

Performs model-free reinforcement learning in R. This implementation enables the learning
    of an optimal policy based on sample sequences consisting of states, actions and rewards. In 
    addition, it supplies multiple predefined reinforcement learning algorithms, such as experience 
    replay. Methodological details can be found in Sutton and Barto (1998) <ISBN:0262039249>.

Functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <https://www.wiley.com/en-us/Reinsurance%3A+Actuarial+and+Statistical+Aspects-p-9780470772683>.