Publication: A bayesian model of covid-19 cases based on the gompertz curve
dc.affiliation.instituto | UC3M. Instituto UC3M - Santander de Big Data | es |
dc.contributor.author | Berihuete, Ángel | |
dc.contributor.author | Sánchez Sánchez , Marta | |
dc.contributor.author | Suárez-Llorens, Alfonso | |
dc.contributor.funder | Ministerio de Economía y Competitividad (España) | es |
dc.date.accessioned | 2021-09-23T08:20:02Z | |
dc.date.available | 2021-09-23T08:20:02Z | |
dc.date.issued | 2021-02-01 | |
dc.description | This article belongs to the Special Issue Stochastic Models with Applications | en |
dc.description.abstract | The COVID-19 pandemic has highlighted the need for finding mathematical models to forecast the evolution of the contagious disease and evaluate the success of particular policies in reducing infections. In this work, we perform Bayesian inference for a non-homogeneous Poisson process with an intensity function based on the Gompertz curve. We discuss the prior distribution of the parameter and we generate samples from the posterior distribution by using Markov Chain Monte Carlo (MCMC) methods. Finally, we illustrate our method analyzing real data associated with COVID-19 in a specific region located at the south of Spain. | en |
dc.description.sponsorship | This research was funded by the Ministerio de Economía y Competitividad (Spain), under grant number MTM2017-89577-P, by the 2014-2020 ERDF Operational Programme and by the Consejería de Economía, Conocimiento, Empresas y Universidad (Junta de Andalucía, Spain), under grant: FEDER-UCA18-107519. | en |
dc.format.extent | 16 | |
dc.identifier.bibliographicCitation | Berihuete, N., Sánchez-Sánchez, M. & Suárez-Llorens, A. (2021). A Bayesian Model of COVID-19 Cases Based on the Gompertz Curve. Mathematics, 9(3), 228. | en |
dc.identifier.doi | https://doi.org/10.3390/math9030228 | |
dc.identifier.issn | 2227-7390 | |
dc.identifier.publicationfirstpage | 228 | |
dc.identifier.publicationissue | 3 | |
dc.identifier.publicationtitle | Mathematics | en |
dc.identifier.publicationvolume | 9 | |
dc.identifier.uri | https://hdl.handle.net/10016/33307 | |
dc.identifier.uxxi | AR/0000028264 | |
dc.language.iso | eng | |
dc.publisher | MDPI | en |
dc.relation.projectID | Gobierno de España. MTM2017-89577-P | es |
dc.rights | © 2021 by the authors. | en |
dc.rights | Atribución 3.0 España | * |
dc.rights.accessRights | open access | en |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject.eciencia | Matemáticas | es |
dc.subject.other | Bayesian inference | en |
dc.subject.other | Gompertz curve | en |
dc.subject.other | Inverse gaussian | en |
dc.subject.other | Modeling epidemics | en |
dc.subject.other | Non-homogeneous poisson process | en |
dc.title | A bayesian model of covid-19 cases based on the gompertz curve | en |
dc.type | research article | * |
dc.type.hasVersion | VoR | * |
dspace.entity.type | Publication |
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