Learning Sparse Log-Ratios for Compositional Data
c(
person("Elliott", "Gordon-Rodriguez", email = "eg2912@columbia.edu", role = c("aut", "cre")),
person("Thomas", "Quinn", email = "contacttomquinn@gmail.com", role = c("aut"))
)
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.
zCompositions, testthat (>= 2.1.0), knitr, rmarkdown
Elliott Gordon-Rodriguez [aut, cre],
Thomas Quinn [aut]

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

Transformation-Free Linear Regression for Compositional Outcomes
and Predictors
c(person(given = "Jacob",
family = "Fiksel",
role = c("aut", "cre"),
email = "jfiksel@gmail.com",
comment = c(ORCID = "0000-0001-7067-1334")),
person(given = "Abhirup",
family = "Datta",
role = c("ctb"),
email = "abhidatta@jhu.edu"))
Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2020) <arXiv:2004.07881>
for transformation-free linear regression for compositional outcomes and predictors.
SQUAREM (>= 2020.3), future, future.apply
knitr, ggtern, gtools, remotes, testthat, markdown
Jacob Fiksel [aut, cre] (<https://orcid.org/0000-0001-7067-1334>),
Abhirup Datta [ctb]

c(person(given = "Jacob",
family = "Fiksel",
role = c("aut", "cre"),
email = "jfiksel@gmail.com",
comment = c(ORCID = "0000-0001-7067-1334")),
person(given = "Abhirup",
family = "Datta",
role = "aut",
email = "abhidatta@jhu.edu"))
Implements the expectation-maximization (EM) algorithm as described in Fiksel et al. (2021) <doi:10.1111/biom.13465>
for transformation-free linear regression for compositional outcomes and predictors.
knitr, robCompositions, gtools, remotes, testthat, markdown
Jacob Fiksel [aut, cre] (<https://orcid.org/0000-0001-7067-1334>),
Abhirup Datta [aut]