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BayCANN: Streamlining Bayesian Calibration With Artificial Neural Network Metamodeling
Purpose: Bayesian calibration is generally superior to standard direct-search algorithms in that it estimates the full joint posterior distribution of the calibrated parameters. However, there are many barriers to using Bayesian calibration in health decision sciences stemming from the need to progr...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185956/ https://www.ncbi.nlm.nih.gov/pubmed/34113262 http://dx.doi.org/10.3389/fphys.2021.662314 |