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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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| Vydáno v: | J Comput Graph Stat |
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| Hlavní autoři: | , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2020
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| Témata: | |
| On-line přístup: | 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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