Package: marble 0.0.3

Xi Lu

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++'.

Authors:Xi Lu [aut, cre], Cen Wu [aut]

marble_0.0.3.tar.gz
marble_0.0.3.tar.gz(r-4.5-noble)marble_0.0.3.tar.gz(r-4.4-noble)
marble_0.0.3.tgz(r-4.4-emscripten)marble_0.0.3.tgz(r-4.3-emscripten)
marble.pdf |marble.html
marble/json (API)

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

Peer review:

Bug tracker:https://github.com/xilustat/marble/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • E - Simulated data for demonstrating the features of marble.
  • X - Simulated data for demonstrating the features of marble.
  • Y - Simulated data for demonstrating the features of marble.
  • clin - Simulated data for demonstrating the features of marble.

openblascppopenmp

1.00 score 2 scripts 186 downloads 2 exports 2 dependencies

Last updated 8 months agofrom:9d9b24529f. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 01 2024
R-4.5-linux-x86_64OKDec 01 2024

Exports:GxESelectionmarble

Dependencies:RcppRcppArmadillo