Source: Nonlinear Dynamics. Unidade: IFSC
Subjects: INFERÊNCIA BAYESIANA, SURTOS DE DOENÇAS, COVID-19, CORONAVIRUS
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ABNT
MIRANDA, João Pedro Valeriano et al. Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting. Nonlinear Dynamics, v. 111, n. Ja 2023, p. 549-558 + supplementary information: 1-31, 2023Tradução . . Disponível em: https://doi.org/10.1007/s11071-022-07865-x. Acesso em: 25 abr. 2026.APA
Miranda, J. P. V., Cintra, P. H. P., Libotte, G. B., Reis, I., Fontinele, F., Silva, R. S., & Malta, S. M. C. (2023). Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting. Nonlinear Dynamics, 111( Ja 2023), 549-558 + supplementary information: 1-31. doi:10.1007/s11071-022-07865-xNLM
Miranda JPV, Cintra PHP, Libotte GB, Reis I, Fontinele F, Silva RS, Malta SMC. Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting [Internet]. Nonlinear Dynamics. 2023 ; 111( Ja 2023): 549-558 + supplementary information: 1-31.[citado 2026 abr. 25 ] Available from: https://doi.org/10.1007/s11071-022-07865-xVancouver
Miranda JPV, Cintra PHP, Libotte GB, Reis I, Fontinele F, Silva RS, Malta SMC. Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting [Internet]. Nonlinear Dynamics. 2023 ; 111( Ja 2023): 549-558 + supplementary information: 1-31.[citado 2026 abr. 25 ] Available from: https://doi.org/10.1007/s11071-022-07865-x
