Hybrid algorithms for generating optimal designs for discriminating multiple nonlinear models under various error distributional assumptions

Finding a model-based optimal design that can optimally discriminate among a class of plausible models is a difficult task because the design criterion is non-differentiable and requires 2 or more layers of nested optimization. We propose hybrid algorithms based on particle swarm optimization (PSO)...

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Detalles Bibliográficos
Autores principales: Chen, Ray-Bing, Chen, Ping-Yang, Hsu, Cheng-Lin, Wong, Weng Kee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535070/
https://www.ncbi.nlm.nih.gov/pubmed/33017415
http://dx.doi.org/10.1371/journal.pone.0239864

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535070/
https://www.ncbi.nlm.nih.gov/pubmed/33017415
http://dx.doi.org/10.1371/journal.pone.0239864

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