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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Bibliografische gegevens
Hoofdauteurs: Jieyi Yi, Niansheng Tang
Formaat: Artikel
Taal:English
Gepubliceerd in: MDPI AG 2022-01-01
Reeks:Mathematics
Onderwerpen:
Bayesian lasso
evidence lower bound
high-dimensional linear mixed model
spike and slab priors
variational Bayesian inference
Online toegang:https://www.mdpi.com/2227-7390/10/3/463

Internet

https://www.mdpi.com/2227-7390/10/3/463

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