'GitHub' apps provide a powerful way to manage fine grained
    programmatic access to specific 'git' repositories, without having to
    create dummy users, and which are safer than a personal access token
    for automated tasks. This package extends the 'gh' package to let you
    authenticate and interact with 'GitHub' <https://docs.github.com/en/rest/overview>
    in 'R' as an app.

Functions are provided for quantifying evolution and selection on complex traits. 
              The package implements effective handling and analysis algorithms scaled for 
              genome-wide data and calculates a composite statistic, denoted Ghat, which is used 
              to test for selection on a trait. The package provides a number of simple examples 
              for handling and analysing the genome data and visualising the output and results. 
              Beissinger et al., (2018) <doi:10.1534/genetics.118.300857>.

Interface for the GitHub API that enables efficient 
    management of courses on GitHub. It has a functionality for 
    managing organizations, teams, repositories, and users on GitHub 
    and helps automate most of the tedious and repetitive tasks 
    around creating and distributing assignments.

A statistical hypothesis test for conditional independence.
    Given residuals from a sufficiently powerful regression, it tests whether 
    the covariance of the residuals is vanishing. It can be applied to both
    discretely-observed functional data and multivariate data. 
    Details of the method can be found in Anton Rask Lundborg, Rajen D. Shah and Jonas
    Peters (2022) <doi:10.1111/rssb.12544>.

The goal of 'GHCNr' is to provide a fast and friendly interface with the Global Historical Climatology Network daily (GHCNd) database, which contains daily summaries of weather station data worldwide (<https://www.ncei.noaa.gov/products/land-based-station/global-historical-climatology-network-daily>). GHCNd is accessed through the web API <https://www.ncei.noaa.gov/access/services/data/v1>. 'GHCNr' main functionalities consist of downloading data from GHCNd, filter it, and to aggregate it at monthly and annual scales.