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Joint Bayesian variable and graph selection for regression models with network-structured predictors
In this work, we develop a Bayesian approach to perform selection of predictors that are linked within a network. We achieve this by combining a sparse regression model relating the predictors to a response variable with a graphical model describing conditional dependencies among the predictors. The...
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| Pubblicato in: | Stat Med |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2015
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4775388/ https://ncbi.nlm.nih.gov/pubmed/26514925 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.6792 |
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