gesso: Hierarchical GxE Interactions in a Regularized Regression Model

The method focuses on a single environmental exposure and induces a main-effect-before-interaction hierarchical structure for the joint selection of interaction terms in a regularized regression model. For details see Zemlianskaia et al. (2021) <doi:10.48550/arXiv.2103.13510>.

Version:	1.0.2
Depends:	dplyr, R (≥ 3.5)
Imports:	Rcpp (≥ 1.0.3), Matrix, bigmemory, methods
LinkingTo:	Rcpp, RcppEigen, RcppThread, BH, bigmemory
Suggests:	glmnet, testthat, knitr, rmarkdown, ggplot2
Published:	2021-11-30
DOI:	10.32614/CRAN.package.gesso
Author:	Natalia Zemlianskaia
Maintainer:	Natalia Zemlianskaia <natasha.zemlianskaia at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	yes
Materials:	README
CRAN checks:	gesso results

Documentation:

Reference manual:	gesso.html , gesso.pdf
Vignettes:	Getting started with 'gesso' (source, R code)

Downloads:

Package source:	gesso_1.0.2.tar.gz
Windows binaries:	r-devel: gesso_1.0.2.zip, r-release: gesso_1.0.2.zip, r-oldrel: gesso_1.0.2.zip
macOS binaries:	r-release (arm64): gesso_1.0.2.tgz, r-oldrel (arm64): gesso_1.0.2.tgz, r-release (x86_64): gesso_1.0.2.tgz, r-oldrel (x86_64): gesso_1.0.2.tgz
Old sources:	gesso archive

Linking:

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