Various algorithms related to linguistic fuzzy logic: mining for linguistic fuzzy association
rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD),
and forecasting time-series using fuzzy rule-based ensemble (FRBE). The package also contains basic
fuzzy-related algebraic functions capable of handling missing values in different styles (Bochvar,
Sobocinski, Kleene etc.), computation of Sugeno integrals and fuzzy transform.

Kevin Caye <kevin.caye@gmail.com>
Basile Jumentier <basile.jumentier@gmail.com>
Olivier François <olivier.francois@univ-grenoble-alpes.fr>
Fast and accurate inference of
gene-environment associations (GEA) in genome-wide studies
(Caye et al., 2019, <doi:10.1093/molbev/msz008>).
We developed a least-squares estimation approach for confounder and effect sizes
estimation that provides a unique framework for several categories of genomic data,
not restricted to genotypes.
The speed of the new algorithm is several times faster than the existing GEA approaches,
then our previous version of the 'LFMM' program present in the 'LEA' package
(Frichot and Francois, 2015, <doi:10.1111/2041-210X.12382>).
foreach, rmarkdown, knitr, MASS, RSpectra, stats, ggplot2,
readr, methods, purrr, Rcpp

c(person(given = "Basile",
family = "Jumentier",
role = c("aut", "cre"),
email = "basile.jumentier@gmail.com"),
person(given = "Kevin",
family = "Caye",
role = "ctb",
email = "kevin.caye@gmail.com"),
person(given = "Olivier",
family = "François",
role = "ctb",
email = "olivier.francois@univ-grenoble-alpes.fr"))
Basile Jumentier [aut, cre],
Kevin Caye [ctb],
Olivier François [ctb]

Calculates Low Flow Statistics for daily stream flow data
The "Manual on Low-flow Estimation and Prediction",
published by the World Meteorological Organisation (WMO), gives
an idea how to analyse stream flow data focusing on low-flow
issues. This packages gives functions to compute the described
statistics and produce plots similar to the one in the manual.
R (>= 2.10), lattice, lmom, lmomRFA, latticeExtra