Maximum likelihood estimation for a stochastic SEIR system with a COVID-19 application-Reference-Cited by-同舟云学术

Maximum likelihood estimation for a stochastic SEIR system with a COVID-19 application

Published:2022-11-28 Issue: Volume: Page:1-23
ISSN:0020-7160
Container-title:International Journal of Computer Mathematics
language:en
Short-container-title:International Journal of Computer Mathematics

Author:

Baltazar-Larios Fernando¹^ORCID,Delgado-Vences Francisco²^ORCID,Diaz-Infante Saul³^ORCID

Affiliation:

1. Departamento de Matemáticas, Facultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad de México, México

2. CONACYT – Instituto de Matemáticas, Universidad Nacional Autónoma de México, Oaxaca de Juarez, México

3. Departamento de Matemáticas, CONACYT – Universidad de Sonora, Hermosillo, México

Funder

UNAM-DGAPA-PAPIIT

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207160.2022.2148316

Reference39 articles.

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3. X. Han and P.E. Kloeden, Random Ordinary Differential Equations and their Numerical Solution, Probability Theory and Stochastic Modelling, Vol. 85, Springer, Singapore, 2017.

4. S.M. Iacus, Simulation and Inference for Stochastic Differential Equations: With R Examples, Springer Series in Statistics, Springer, New York, 2008.

5. Parameter estimation for the stochastic SIS epidemic model