Package: roben 0.1.1
roben: Robust Bayesian Variable Selection for Gene-Environment Interactions
Gene-environment (G×E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G×E studies have been commonly encountered, leading to the development of a broad spectrum of robust penalization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a robust Bayesian variable selection method for G×E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects. An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++.
Authors:
roben_0.1.1.tar.gz
roben_0.1.1.zip(r-4.5)roben_0.1.1.zip(r-4.4)roben_0.1.1.zip(r-4.3)
roben_0.1.1.tgz(r-4.4-x86_64)roben_0.1.1.tgz(r-4.4-arm64)roben_0.1.1.tgz(r-4.3-x86_64)roben_0.1.1.tgz(r-4.3-arm64)
roben_0.1.1.tar.gz(r-4.5-noble)roben_0.1.1.tar.gz(r-4.4-noble)
roben_0.1.1.tgz(r-4.4-emscripten)roben_0.1.1.tgz(r-4.3-emscripten)
roben.pdf |roben.html✨
roben/json (API)
# Install 'roben' in R: |
install.packages('roben', repos = c('https://jrhub.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jrhub/roben/issues
- E - Simulated data for demonstrating the features of roben
- E2 - Simulated data for demonstrating the features of roben
- X - Simulated data for demonstrating the features of roben
- X2 - Simulated data for demonstrating the features of roben
- Y - Simulated data for demonstrating the features of roben
- Y2 - Simulated data for demonstrating the features of roben
- clin - Simulated data for demonstrating the features of roben
- clin2 - Simulated data for demonstrating the features of roben
- coeff - Simulated data for demonstrating the features of roben
- coeff2 - Simulated data for demonstrating the features of roben
Last updated 9 months agofrom:5a62e17995. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win-x86_64 | OK | Nov 07 2024 |
R-4.5-linux-x86_64 | OK | Nov 07 2024 |
R-4.4-win-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-aarch64 | OK | Nov 07 2024 |
R-4.3-win-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-aarch64 | OK | Nov 07 2024 |
Exports:GxESelectionroben
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
roben: Robust Bayesian Variable Selection for Gene-Environment Interactions | roben-package |
simulated data for demonstrating the features of roben | clin clin2 coeff coeff2 data E E2 GxE_large GxE_small X X2 Y Y2 |
Variable selection for a roben object | GxESelection GxESelection.NonSparse GxESelection.Sparse |
make predictions from a roben object | predict.roben |
print a GxESelection object | print.GxESelection |
print a roben object | print.roben |
print a roben.pred object | print.roben.pred |
fit a robust Bayesian variable selection | roben |