NAGIOS: RODERIC FUNCIONANDO

Random resampling numerical simulations applied to a SEIR compartmental model

Repositori DSpace/Manakin

dc.contributor.author	Morillas Jurado, Francisco Gabriel
dc.contributor.author	Valero, José
dc.date.accessioned	2022-05-02T13:40:08Z
dc.date.available	2022-05-02T13:40:08Z
dc.date.issued	2021
dc.identifier.citation	Morillas Jurado, Francisco Gabriel Valero, José 2021 Random resampling numerical simulations applied to a SEIR compartmental model European Physical Journal Plus 136 10 1067
dc.identifier.uri	https://hdl.handle.net/10550/82500
dc.description.abstract	In this paper, we apply resampling techniques to a modified compartmental SEIR model which takes into account the existence of undetected infected people in an epidemic. In particular, we implement numerical simulations for the evolution of the first wave of the COVID-19 pandemic in Spain in 2020. We show, by using suitable measures of goodness, that the point estimates obtained by the bootstrap samples improve the ones of the original data. For example, the relative error of detected currently infected people is equal to 0.061 for the initial estimates, while it is reduced to 0.0538 for the mean over all bootstrap estimated series.
dc.relation.ispartof	European Physical Journal Plus, 2021, vol. 136, num. 10, p. 1067
dc.subject	Economia de la salut
dc.subject	Salut pública
dc.title	Random resampling numerical simulations applied to a SEIR compartmental model
dc.type	journal article	es_ES
dc.date.updated	2022-05-02T13:40:09Z
dc.identifier.doi	10.1140/epjp/s13360-021-02003-9
dc.identifier.idgrec	150207
dc.rights.accessRights	open access	es_ES