A Bayesian model calibration framework for stochastic compartmental models with both time-varying and time-invariant parameters-Reference-Cited by-同舟云学术

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A Bayesian model calibration framework for stochastic compartmental models with both time-varying and time-invariant parameters

Published:2024-12 Issue:4 Volume:9 Page:1224-1249
ISSN:2468-0427
Container-title:Infectious Disease Modelling
language:en
Short-container-title:Infectious Disease Modelling

Author:

Robinson Brandon^ORCID,Bisaillon Philippe,Edwards Jodi D.,Kendzerska Tetyana^ORCID,Khalil Mohammad^ORCID,Poirel Dominique,Sarkar Abhijit

Publisher

Elsevier BV

Reference49 articles.

1. Tracking R of COVID-19: A new real-time estimation using the Kalman filter;Arroyo-Marioli;PLoS One,2021

2. Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation;Beck;Journal of Engineering Mechanics,2002

3. Robust bayesian state and parameter estimation framework for stochastic dynamical systems with combined time-varying and time-invariant parameters;Bisaillon;Journal of Sound and Vibration,2024

4. Bayesian parameter estimation and model selection for strongly nonlinear dynamical systems;Bisaillon;Nonlinear Dynamics,2015

5. Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian inference;Bisaillon;Journal of Sound and Vibration,2022

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