zoo, plyr, jpeg, stringr (>= 1.0.0), bcp, strucchange,
parallel, foreach, doParallel, iterators, gtools, raster, sp

c(
person('Jake', 'Hughey', , 'jakejhughey@gmail.com', c('aut', 'cre')),
person('Layla', 'Aref', , 'larefnezhad@gmail.com', 'aut'))
Use phenotype risk scores based on linked clinical and genetic data
to study Mendelian disease and rare genetic variants. See Bastarache et al.
2018 <doi:10.1126/science.aal4043>.
Jake Hughey [aut, cre],
Layla Aref [aut]

doParallel (>= 1.0.17), knitr, rmarkdown, testthat (>=
3.1.0), qs (>= 0.25.2)

Analysis of features by phi delta diagrams. In particular, functions for reading data and calculating phi and delta as well as the functionality to plot it. Moreover it is possible to do further analysis on the data by generating rankings. For more information on phi delta diagrams, see also Giuliano Armano (2015) <doi:10.1016/j.ins.2015.07.028>.

Analysis of terms in linear and generalized linear models,
on the basis of multiple comparisons of factor contrasts.
Specially suited for the analysis of interaction terms.

Analysis of terms in linear, generalized and mixed linear
models, on the basis of multiple comparisons of factor
contrasts.  Specially suited for the analysis of interaction
terms.

Analysis of terms in linear, generalized and mixed linear models,
on the basis of multiple comparisons of factor contrasts.  Specially suited
for the analysis of interaction terms.

c(person("Helios", "De Rosario-Martinez", role=c("aut", "cre"),
email="helios.derosario@gmail.com"),
person("John", "Fox", role="ctb"),
person("R Core Team", role="ctb"))
Helios De Rosario-Martinez [aut, cre],
John Fox [ctb],
R Core Team [ctb]

Similarity and Distance Quantification Between Probability
Functions
Computes 46 optimized distance and similarity measures for comparing probability functions. These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a base framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.