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Bayesian variable selection in linear quantile mixed models for longitudinal data with application to macular degeneration
This paper presents a Bayesian analysis of linear mixed models for quantile regression based on a Cholesky decomposition for the covariance matrix of random effects. We develop a Bayesian shrinkage approach to quantile mixed regression models using a Bayesian adaptive lasso and an extended Bayesian...
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| Pubblicato in: | PLoS One |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7588124/ https://ncbi.nlm.nih.gov/pubmed/33104698 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0241197 |
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