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  "Description": "Implements variational Bayesian algorithms to perform\nscalable variable selection for sparse, high-dimensional linear\nand logistic regression models. Features include a novel\nprioritized updating scheme, which uses a preliminary estimator\nof the variational means during initialization to generate an\nupdating order prioritizing large, more relevant, coefficients.\nSparsity is induced via spike-and-slab priors with either\nLaplace or Gaussian slabs. By default, the heavier-tailed\nLaplace density is used. Formal derivations of the algorithms\nand asymptotic consistency results may be found in Kolyan Ray\nand Botond Szabo (2020) <doi:10.1080/01621459.2020.1847121> and\nKolyan Ray, Botond Szabo, and Gabriel Clara (2020)\n<arXiv:2010.11665>.",
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