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

gesso_1.0.2.tar.gz
gesso_1.0.2.tar.gz(r-4.5-noble)gesso_1.0.2.tar.gz(r-4.4-noble)
gesso_1.0.2.tgz(r-4.4-emscripten)gesso_1.0.2.tgz(r-4.3-emscripten)
gesso.pdf |gesso.html✨
gesso/json (API)

# Install 'gesso' in R:

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

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.

7 exports 0.00 score 25 dependencies 7 scripts 285 downloads

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

Target	Result	Date
Doc / Vignettes	OK	Sep 06 2024
R-4.5-linux-x86_64	NOTE	Sep 06 2024

Exports:data.gen gesso.coef gesso.coefnum gesso.cv gesso.fit gesso.predict selection.metrics

Dependencies:BH bigmemory bigmemory.sri cli dplyr fansi generics glue lattice lifecycle magrittr Matrix pillar pkgconfig R6 Rcpp RcppEigen RcppThread rlang tibble tidyselect utf8 uuid vctrs withr

Getting started with gesso

Natalia Zemlianskaia

Rendered fromvignette.Rmdusingknitr::rmarkdownon Sep 06 2024.

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

Citation

Readme and manuals

Help Manual

Help page	Topics
Hierarchical GxE Interactions in a Regularized Regression Model	gesso-package gesso
Data Generation	data.gen
Get model coefficients	gesso.coef
Get model coefficients with specified number of non-zero interactions	gesso.coefnum
Cross-Validation	gesso.cv
gesso fit	gesso.fit
Predict new outcome vector	gesso.predict
Selection metrics	selection.metrics