Package: sparsevb
Type: Package
Title: Spike-and-Slab Variational Bayes for Linear and Logistic
        Regression
Version: 0.1.0
Date: 2021-1-04
Authors@R: c(person("Gabriel", "Clara", email = "gabriel.j.clara@gmail.com", role = c("aut", "cre")), person("Botond", "Szabo", role = "aut"), person("Kolyan", "Ray", role = "aut"))
Maintainer: Gabriel Clara <gabriel.j.clara@gmail.com>
Description: 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 (2020) <doi:10.1080/01621459.2020.1847121> and
        Kolyan Ray, Botond Szabo, and Gabriel Clara (2020)
        <arXiv:2010.11665>.
BugReports: https://gitlab.com/gclara/varpack/-/issues
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.5), selectiveInference (>= 1.2.5), glmnet (>=
        4.0-2), stats
LinkingTo: Rcpp, RcppArmadillo, RcppEnsmallen
Encoding: UTF-8
RoxygenNote: 7.1.1
Repository: https://gabriel-clara.r-universe.dev
Date/Publication: 2025-01-23 22:27:32 UTC
RemoteUrl: https://gitlab.com/gclara/varpack
RemoteRef: HEAD
RemoteSha: 458c2ef57401c9a1fe806d7087b27a649b54fd7e
NeedsCompilation: yes
Packaged: 2026-10-15 11:27:36 UTC; root
Author: Gabriel Clara [aut, cre],
  Botond Szabo [aut],
  Kolyan Ray [aut]