# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "sparsevb" in publications use:' type: software license: GPL-3.0-or-later title: 'sparsevb: Spike-and-Slab Variational Bayes for Linear and Logistic Regression' version: 0.1.0 doi: 10.32614/CRAN.package.sparsevb abstract: 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) and Kolyan Ray, Botond Szabo, and Gabriel Clara (2020) . authors: - family-names: Clara given-names: Gabriel email: gabriel.j.clara@gmail.com - family-names: Szabo given-names: Botond - family-names: Ray given-names: Kolyan repository: https://gabriel-clara.r-universe.dev repository-code: https://gitlab.com/gclara/varpack commit: 458c2ef57401c9a1fe806d7087b27a649b54fd7e url: https://gitlab.com/gclara/varpack date-released: '2021-01-04' contact: - family-names: Clara given-names: Gabriel email: gabriel.j.clara@gmail.com