Calibration and prediction for the inexact SIR model

Calibration and prediction for the inexact SIR model

A Susceptible Infective Recovered (SIR) model is usually unable to mimic the actual epidemiological system exactly. The reasons for this inaccuracy include observation errors and model discrepancies due to assumptions and simplifications made by the SIR model. Hence, this work proposes calibration a...

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Détails bibliographiques
Auteurs principaux: Yan Wang, Guichen Lu, Jiang Du
Format: Article
Langue:English
Publié: AIMS Press 2022-01-01
Collection:Mathematical Biosciences and Engineering
Sujets:
inexact sir model
gaussian process model
wild bootstrap
uncertainty quantification
heteroscedastic noise
calibration
Accès en ligne:https://www.aimspress.com/article/doi/10.3934/mbe.2022128?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2022128?viewType=HTML

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