Package: emBayes 0.1.6

Yuwen Liu

emBayes: Robust Bayesian Variable Selection via Expectation-Maximization

Variable selection methods have been extensively developed for analyzing highdimensional omics data within both the frequentist and Bayesian frameworks. This package provides implementations of the spike-and-slab quantile (group) LASSO which have been developed along the line of Bayesian hierarchical models but deeply rooted in frequentist regularization methods by utilizing Expectation–Maximization (EM) algorithm. The spike-and-slab quantile LASSO can handle data irregularity in terms of skewness and outliers in response variables, compared to its non-robust alternative, the spike-and-slab LASSO, which has also been implemented in the package. In addition, procedures for fitting the spike-and-slab quantile group LASSO and its non-robust counterpart have been implemented in the form of quantile/least-square varying coefficient mixed effect models for high-dimensional longitudinal data. The core module of this package is developed in 'C++'.

Authors:Yuwen Liu [aut, cre], Cen Wu [aut]

emBayes_0.1.6.tar.gz
emBayes_0.1.6.tar.gz(r-4.5-noble)emBayes_0.1.6.tar.gz(r-4.4-noble)
emBayes_0.1.6.tgz(r-4.4-emscripten)emBayes_0.1.6.tgz(r-4.3-emscripten)
emBayes.pdf |emBayes.html
emBayes/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • data - Simulated gene expression example data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 1 scripts 173 downloads 2 exports 11 dependencies

Last updated 3 months agofrom:98ef0812da. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-linux-x86_64OKNov 14 2024

Exports:cv.emBayesemBayes

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival