FLORAL: Fit Log-Ratio Lasso Regression for Compositional Data

Log-ratio Lasso regression for continuous, binary, and survival outcomes with compositional features. See Fei and others (2023) <doi:10.1101/2023.05.02.538599>.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.9), stats, survival, ggplot2, survcomp, reshape, dplyr, glmnet, caret, grDevices, utils, mvtnorm, doParallel, doRNG, foreach
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: covr, knitr, rmarkdown, spelling, testthat (≥ 3.0.0), patchwork
Published: 2023-07-05
Author: Teng Fei ORCID iD [aut, cre, cph], Tyler Funnell ORCID iD [aut], Nicholas Waters ORCID iD [aut], Sandeep Raj ORCID iD [aut]
Maintainer: Teng Fei <feit1 at mskcc.org>
BugReports: https://github.com/vdblab/FLORAL/issues
License: GPL (≥ 3)
URL: https://vdblab.github.io/FLORAL/
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: FLORAL results

Documentation:

Reference manual: FLORAL.pdf
Vignettes: Using FLORAL for Microbiome Analysis

Downloads:

Package source: FLORAL_0.2.0.tar.gz
Windows binaries: r-prerel: FLORAL_0.2.0.zip, r-release: FLORAL_0.2.0.zip, r-oldrel: FLORAL_0.2.0.zip
macOS binaries: r-prerel (arm64): FLORAL_0.2.0.tgz, r-release (arm64): FLORAL_0.2.0.tgz, r-oldrel (arm64): FLORAL_0.2.0.tgz, r-prerel (x86_64): FLORAL_0.2.0.tgz, r-release (x86_64): FLORAL_0.2.0.tgz
Old sources: FLORAL archive

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