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Regression‐based Bayesian estimation and structure learning for nonparanormal graphical models
A nonparanormal graphical model is a semiparametric generalization of a Gaussian graphical model for continuous variables in which it is assumed that the variables follow a Gaussian graphical model only after some unknown smooth monotone transformations. We consider a Bayesian approach to inference...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Wiley Subscription Services, Inc., A Wiley Company
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455150/ https://www.ncbi.nlm.nih.gov/pubmed/36090618 http://dx.doi.org/10.1002/sam.11576 |