using the log-ratio approach introduced by John Aitchison in 1982. Main functions

using the log-ratio approach introduced by John Aitchison (1982) <http:www.jstor.org/stable/2345821>. Main functions

email = "mcomas@imae.udg.edu", comment = c(ORCID = "0000-0001-9759-0622")))
Author: Marc Comas-Cufí [aut, cre] (<https://orcid.org/0000-0001-9759-0622>)

Suggests: knitr, rmarkdown, testthat (>= 2.1.0), ggplot2

Imports: Rcpp (>= 0.12.12), stats, Matrix, jsonlite
LinkingTo: Rcpp, RcppArmadillo (>= 0.11.2)

Title: Compositional Data Analysis for Microbiome Studies
Description: Functions for microbiome data analysis that take into account its compositional nature. Performs variable selection through penalized regression for both, cross-sectional and longitudinal studies, and for binary and continuous outcomes.
Imports: corrplot, glmnet, plyr, pROC, ggpubr, ggplot2
Author: Malu Calle [aut] (<https://orcid.org/0000-0001-9334-415X>),

Imports: corrplot, glmnet, plyr, pROC, ggpubr, ggplot2, qpdf

Title: Learning Sparse Log-Ratios for Compositional Data
person("Elliott", "Gordon-Rodriguez", email = "eg2912@columbia.edu", role = c("aut", "cre")),
person("Thomas", "Quinn", email = "contacttomquinn@gmail.com", role = c("aut"))
Description: In the context of high-throughput genetic data,
CoDaCoRe identifies a set of sparse biomarkers that are
predictive of a response variable of interest (Gordon-Rodriguez
et al., 2021) <doi:10.1093/bioinformatics/btab645>. More
generally, CoDaCoRe can be applied to any regression problem
where the independent variable is Compositional (CoDa), to
derive a set of scale-invariant log-ratios (ILR or SLR) that
are maximally associated to a dependent variable.
Suggests: zCompositions, testthat (>= 2.1.0), knitr, rmarkdown
Author: Elliott Gordon-Rodriguez [aut, cre],

Title: Markov chain Monte Carlo burn-in based on "bridge" statistics
Author: Yann Richet, Xavier Bay, Olivier Jacquet, Alexis Jinaphanh
Description: Markov chain Monte Carlo burn-in based on "bridge" statistics, in the way of coda::heidel.diag, but including non asymptotic tabulated statistics.