marble: Robust Marginal Bayesian Variable Selection for Gene-Environment Interactions

Recently, multiple marginal variable selection methods have been developed and shown to be effective in Gene-Environment interactions studies. We propose a novel marginal Bayesian variable selection method for Gene-Environment interactions studies. In particular, our marginal Bayesian method is robust to data contamination and outliers in the outcome variables. With the incorporation of spike-and-slab priors, we have implemented the Gibbs sampler based on Markov Chain Monte Carlo. The core algorithms of the package have been developed in 'C++'.

Version: 0.0.3
Depends: R (≥ 3.5.0)
Imports: Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Published: 2024-04-04
Author: Xi Lu [aut, cre], Cen Wu [aut]
Maintainer: Xi Lu <xilu at ksu.edu>
License: GPL-2
URL: https://github.com/xilustat/marble
NeedsCompilation: yes
CRAN checks: marble results

Documentation:

Reference manual: marble.pdf

Downloads:

Package source: marble_0.0.3.tar.gz
Windows binaries: r-devel: marble_0.0.3.zip, r-release: marble_0.0.3.zip, r-oldrel: marble_0.0.3.zip
macOS binaries: r-release (arm64): marble_0.0.3.tgz, r-oldrel (arm64): marble_0.0.3.tgz, r-release (x86_64): marble_0.0.3.tgz
Old sources: marble archive

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