Variational Bayesian Inference in High-Dimensional Linear Mixed Models

Variational Bayesian Inference in High-Dimensional Linear Mixed Models

In high-dimensional regression models, the Bayesian lasso with the Gaussian spike and slab priors is widely adopted to select variables and estimate unknown parameters. However, it involves large matrix computations in a standard Gibbs sampler. To solve this issue, the Skinny Gibbs sampler is employ...

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Dettagli Bibliografici
Autori principali:	Jieyi Yi, Niansheng Tang
Natura:	Articolo
Lingua:	English
Pubblicazione:	MDPI AG 2022-01-01
Serie:	Mathematics
Soggetti:	Bayesian lasso evidence lower bound high-dimensional linear mixed model spike and slab priors variational Bayesian inference
Accesso online:	https://www.mdpi.com/2227-7390/10/3/463

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