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++'.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.3 |
rolling linux/jammy R-4.5 | marble_0.0.3.tar.gz |
179.3 KiB |
0.0.3 |
rolling linux/noble R-4.5 | marble_0.0.3.tar.gz |
186.2 KiB |
0.0.3 |
rolling source/ R- | marble_0.0.3.tar.gz |
40.0 KiB |
0.0.3 |
latest linux/jammy R-4.5 | marble_0.0.3.tar.gz |
179.3 KiB |
0.0.3 |
latest linux/noble R-4.5 | marble_0.0.3.tar.gz |
186.2 KiB |
0.0.3 |
latest source/ R- | marble_0.0.3.tar.gz |
40.0 KiB |
0.0.3 |
2026-04-26 source/ R- | marble_0.0.3.tar.gz |
40.0 KiB |
0.0.3 |
2026-04-23 source/ R- | marble_0.0.3.tar.gz |
40.0 KiB |
0.0.3 |
2026-04-09 windows/windows R-4.5 | marble_0.0.3.zip |
596.3 KiB |
0.0.3 |
2025-04-20 source/ R- | marble_0.0.3.tar.gz |
40.0 KiB |