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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| Päätekijät: | , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2022-01-01
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| Sarja: | Mathematics |
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| Linkit: | https://www.mdpi.com/2227-7390/10/3/463 |
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