https://gabriel-clara.r-universe.devRecent package updates in gabriel-claraR-universehttps://github.com/gabriel-clara.pnghttps://gabriel-clara.r-universe.devThu, 23 Jan 2025 22:27:32 GMTgabriel.j.clara@gmail.com (Gabriel Clara)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>.https://github.com/r-universe/gabriel-clara/actions/runs/26015948558Thu, 23 Jan 2025 22:27:32 GMTsparsevb0.1.0successhttps://gabriel-clara.r-universe.devhttps://gitlab.com/gclara/varpack