Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the “go-to” option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics...

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Detalles Bibliográficos
Autores principales: Burr, Tom, Skurikhin, Alexei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3830866/
https://www.ncbi.nlm.nih.gov/pubmed/24288668
http://dx.doi.org/10.1155/2013/210646

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3830866/
https://www.ncbi.nlm.nih.gov/pubmed/24288668
http://dx.doi.org/10.1155/2013/210646

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