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:
Downloads:
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