Package: gesso 1.0.2

Natalia Zemlianskaia

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) <arxiv:2103.13510>.

Authors:Natalia Zemlianskaia

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gesso/json (API)

# Install 'gesso' in R:
install.packages('gesso', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 7 scripts 207 downloads 7 exports 25 dependencies

Last updated 3 years agofrom:3b8715c6ad. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-linux-x86_64NOTENov 05 2024

Exports:data.gengesso.coefgesso.coefnumgesso.cvgesso.fitgesso.predictselection.metrics

Dependencies:BHbigmemorybigmemory.sriclidplyrfansigenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigR6RcppRcppEigenRcppThreadrlangtibbletidyselectutf8uuidvctrswithr

Getting started with gesso

Natalia Zemlianskaia

Rendered fromvignette.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2021-11-30
Started: 2021-06-07