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Bayesian Variable Selection for Gaussian copula regression models
We develop a novel Bayesian method to select important predictors in regression models with multiple responses of diverse types. A sparse Gaussian copula regression model is used to account for the multivariate dependencies between any combination of discrete and/or continuous responses and their as...
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| Publicat a: | J Comput Graph Stat |
|---|---|
| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7614421/ https://ncbi.nlm.nih.gov/pubmed/37051045 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/10618600.2020.1840997 |
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