Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection.
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ABSTRACT:
SUBMITTER: Song Q
PROVIDER: S-EPMC8302213 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Publications
Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection.
Song Qifan Q Sun Yan Y Ye Mao M Liang Faming F
Biometrika 20200713 4
Stochastic gradient Markov chain Monte Carlo (MCMC) algorithms have received much attention in Bayesian computing for big data problems, but they are only applicable to a small class of problems for which the parameter space has a fixed dimension and the log-posterior density is differentiable with respect to the parameters. This paper proposes an extended stochastic gradient MCMC algorithm which, by introducing appropriate latent variables, can be applied to more general large-scale Bayesian co ...[more]
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