Package: sparsevb 0.1.1

Gabriel Clara

sparsevb: Spike-and-Slab Variational Bayes for Linear and Logistic Regression

Implements variational Bayesian algorithms to perform scalable variable selection for sparse, high-dimensional linear and logistic regression models. Features include a novel prioritized updating scheme, which uses a preliminary estimator of the variational means during initialization to generate an updating order prioritizing large, more relevant, coefficients. Sparsity is induced via spike-and-slab priors with either Laplace or Gaussian slabs. By default, the heavier-tailed Laplace density is used. Formal derivations of the algorithms and asymptotic consistency results may be found in Kolyan Ray and Botond Szabo (JASA 2020) and Kolyan Ray, Botond Szabo, and Gabriel Clara (NeurIPS 2020).

Authors:Gabriel Clara [aut, cre], Botond Szabo [aut], Kolyan Ray [aut]

sparsevb_0.1.1.tar.gz
sparsevb_0.1.1.tar.gz(r-4.5-noble)sparsevb_0.1.1.tar.gz(r-4.4-noble)
sparsevb_0.1.1.tgz(r-4.4-emscripten)sparsevb_0.1.1.tgz(r-4.3-emscripten)
sparsevb.pdf |sparsevb.html✨
sparsevb/json (API)

# Install 'sparsevb' in R:
install.packages('sparsevb', repos = 'https://cloud.r-project.org')

Bug tracker:https://gitlab.com/gclara/varpack

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

1.00 score 199 downloads 1 exports 18 dependencies

Last updated 2 months agofrom:eb538d4b3a. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 25 2025
R-4.5-linux-x86_64OKMar 25 2025
R-4.4-linux-x86_64OKMar 25 2025

Exports:svb.fit

Dependencies:adaptMCMCcodacodetoolsforeachglmnetintervalsiteratorslatticeMASSMatrixramcmcRcppRcppArmadilloRcppEigenRcppEnsmallenselectiveInferenceshapesurvival

Citation

To cite package ‘sparsevb’ in publications use:

Clara G, Szabo B, Ray K (2025). sparsevb: Spike-and-Slab Variational Bayes for Linear and Logistic Regression. R package version 0.1.1, https://CRAN.R-project.org/package=sparsevb.

Corresponding BibTeX entry: 

  @Manual{,
    title = {sparsevb: Spike-and-Slab Variational Bayes for Linear and
      Logistic Regression},
    author = {Gabriel Clara and Botond Szabo and Kolyan Ray},
    year = {2025},
    note = {R package version 0.1.1},
    url = {https://CRAN.R-project.org/package=sparsevb},
  }