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Stochastic approximation cut algorithm for inference in modularized Bayesian models
Bayesian modelling enables us to accommodate complex forms of data and make a comprehensive inference, but the effect of partial misspecification of the model is a concern. One approach in this setting is to modularize the model and prevent feedback from suspect modules, using a cut model. After obs...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612314/ https://www.ncbi.nlm.nih.gov/pubmed/35125678 http://dx.doi.org/10.1007/s11222-021-10070-2 |