Performs family-based association tests with a polytomous outcome under 2-locus and 1-locus models
             defined by some design matrix.

Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.

Kiener distributions K1, K2, K3, K4 and K7 to characterize
    distributions with left and right, symmetric or asymmetric fat tails in 
    finance, neuroscience and other disciplines. Two algorithms to estimate the
    distribution parameters, quantiles, value-at-risk and expected shortfall.
    IMPORTANT: Standardization has been changed in versions >= 2.0.0 to get 
	sd = 1 when kappa = Inf rather than 2*pi/sqrt(3) in versions <= 1.8.6. 
	This affects parameter g (other parameters stay unchanged). Do not update 
	if you need consistent comparisons with previous results for the g parameter.

A collection of functions designed to retrieve, filter and spatialize data from the Catálogo Taxônomico da Fauna do Brasil. For more information about the dataset, please visit <https://fauna.jbrj.gov.br/fauna/listaBrasil/>.

Create datasets with factorial structure through simulation by specifying variable parameters. Extended documentation at <https://www.scienceverse.org/faux/>. Described in DeBruine (2020) <doi:10.5281/zenodo.2669586>.

Provides a replacement for dplyr::na_if().  Allows you to
    specify multiple values to be replaced with NA using a single
    function.

HTTP error helpers. Methods included for general purpose HTTP
    error handling, as well as individual methods for every HTTP status
    code, both via status code numbers as well as their descriptive names.
    Supports ability to adjust behavior to stop, message or warning.
    Includes ability to use custom whisker template to have any configuration
    of status code, short description, and verbose message. Currently
    supports integration with 'crul', 'curl', and 'httr'.

Implements the statistic FAVA, an Fst-based Assessment of Variability across 
  vectors of relative Abundances, as well as a suite of helper functions which enable the 
  visualization and statistical analysis of relative abundance data. The 'FAVA' R package 
  accompanies the paper, “Quantifying compositional variability in microbial communities
  with FAVA” by Morrison, Xue, and Rosenberg (2025) <doi:10.1073/pnas.2413211122>.