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Large-Scale Bayesian Variable Selection Using Variational Methods
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | varbvs |
Large-Scale Bayesian Variable Selection Using Variational Methods |
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31 May 2023
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Fast algorithms for fitting Bayesian variable selection models and computing Bayes factors, in which the outcome (or response variable) is modeled using a linear regression or a logistic regression. The algorithms are based on the variational approximations described in "Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies" (P. Carbonetto & M. Stephens, 2012, <doi:10.1214/12-BA703>). This software has been applied to large data sets with over a million variables and thousands of samples.
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