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...

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Detalles Bibliográficos
Autores principales: Jalal, Hawre, Trikalinos, Thomas A., Alarid-Escudero, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Physiology
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

Internet

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

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