Semi-analytical hierarchical Bayesian inference of nonlinear model structure in stochastic dynamics: Applied to compartmental models of infectious diseases.

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Bibliographic Details
Title: Semi-analytical hierarchical Bayesian inference of nonlinear model structure in stochastic dynamics: Applied to compartmental models of infectious diseases.
Authors: Robinson B; Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada.; University of Ottawa Heart Institute, Ottawa, Ontario, Canada., Bisaillon P; Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada., Sandhu R; Computational Science Center, National Laboratory of the Rockies, Golden, Colorado, United States of America., Khalil M; Quantitative Modeling & Analysis Department, Sandia National Laboratories, Livermore, California, United States of America., Edwards JD; University of Ottawa Heart Institute, Ottawa, Ontario, Canada.; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.; ICES, Ottawa, Ontario, Canada., Kendzerska T; ICES, Ottawa, Ontario, Canada.; The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.; Department of Medicine, Faculty of Medicine, Division of Respirology, University of Ottawa, Ottawa, Ontario, Canada., Walker T; Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada., Mills S; School of Mathematics and Statistics, Carleton University, Ottawa, Ontario, Canada., Pettit C; Aerospace Engineering Department, United States Naval Academy, Annapolis, Maryland, United States of America., Poirel D; Department of Mechanical and Aerospace Engineering, Royal Military College of Canada, Kingston, Ontario, Canada., Sarkar A; Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada.
Source: PloS one [PLoS One] 2026 Jul 10; Vol. 21 (7), pp. e0350747. Date of Electronic Publication: 2026 Jul 10 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1932-6203
DOI:10.1371/journal.pone.0350747