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 + fileLICENSE |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | gesso results[issues need fixing before 2025-12-18] |
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