'Guild AI' is an open-source tool for managing machine learning
    experiments. It's for scientists, engineers, and researchers who want to
    run scripts, compare results, measure progress, and automate machine
    learning workflow. 'Guild AI' is a light weight, external tool that runs
    locally. It works with any framework, doesn't require any changes to
    your code, or access to any web services. Users can easily record
    experiment metadata, track model changes, manage experiment artifacts,
    tune hyperparameters, and share results. 'Guild AI' combines features
    from 'Git', 'SQLite', and 'Make' to provide a lab notebook for machine
    learning.

A collection of sampling formulas for the unified neutral model of biogeography and biodiversity. Alongside the sampling formulas, it includes methods to perform maximum likelihood optimization of the sampling formulas, methods to generate data given the neutral model, and methods to estimate the expected species abundance distribution. Sampling formulas included in the GUILDS package are the Etienne Sampling Formula (Etienne 2005), the guild sampling formula, where guilds are assumed to differ in dispersal ability (Janzen et al. 2015), and  the guilds sampling formula conditioned on guild size (Janzen et al. 2015).

Create a user-friendly plotting GUI for 'R'.
    In addition, one purpose of creating the 'R' package is to facilitate third-party software to call 'R' for drawing, for example, 'Phoenix WinNonlin' software calls 'R' to draw the drug concentration versus time curve.

Show graphically the results of profiling R functions by tracking their execution time.

This 'R' package provides a single procedure guix.install(),
  which allows users to install 'R' packages via 'Guix' right from within
  their running 'R' session.  If the requested 'R' package does not exist
  in 'Guix' at this time, the package and all its missing dependencies
  will be imported recursively and the generated package definitions
  will be written to ~/.Rguix/packages.scm.  This record of imported
  packages can be used later to reproduce the environment, and to add
  the packages in question to a proper 'Guix' channel (or 'Guix' itself).
  guix.install() not only supports installing packages from CRAN, but
  also from Bioconductor or even arbitrary 'git' or 'mercurial'
  repositories, replacing the need for installation via 'devtools'.