Simplified scenario testing and sensitivity analysis,
    redesigned to use packages 'future' and 'furrr'. Provides
    functions for generating function argument sets using
    one-factor-at-a-time (OFAT) and (sampled) permutations.

Provides functions for the Bayesian analysis of extreme value
    models.  The 'rust' package <https://cran.r-project.org/package=rust> is
    used to simulate a random sample from the required posterior distribution.
    The functionality of 'revdbayes' is similar to the 'evdbayes' package
    <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain
    Monte Carlo ('MCMC') methods for posterior simulation.  In addition, there
    are functions for making inferences about the extremal index, using 
    the models for threshold inter-exceedance times of Suveges and Davison 
    (2010) <doi:10.1214/09-AOAS292> and Holesovsky and Fusek (2020) 
    <doi:10.1007/s10687-020-00374-3>. Also provided are d,p,q,r functions for 
    the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') 
    distributions that deal appropriately with cases where the shape parameter 
    is very close to zero.

Computation of (direct and indirect) revealed preferences, fast non-parametric tests of rationality axioms (WARP, SARP, GARP), simulation of axiom-consistent data, and detection of axiom-consistent subpopulations. Rationality tests follow Varian (1982) <doi:10.2307/1912771>, axiom-consistent subpopulations follow Crawford and Pendakur (2012) <doi:10.1111/j.1468-0297.2012.02545.x>.

R Markdown format for 'reveal.js' presentations, a framework 
  for easily creating beautiful presentations using HTML.

An implementation of the reverse ecology framework. Reverse ecology
    refers to the use of genomics to study ecology with no a priori assumptions
    about the organism(s) under consideration, linking organisms to their
    environment. It allows researchers to reconstruct the metabolic networks and
    study the ecology of poorly characterized microbial species from their
    genomic information, and has substantial potentials for microbial community
    ecological analysis.