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Computing the density function of complex models with randomness by using polynomial expansions and the RVT technique. Application to the SIR epidemic model

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Computing the density function of complex models with randomness by using polynomial expansions and the RVT technique. Application to the SIR epidemic model

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dc.contributor.author Calatayud, Julia es_ES
dc.contributor.author Cortés, J.-C. es_ES
dc.contributor.author Jornet, Marc es_ES
dc.date.accessioned 2021-02-09T04:31:29Z
dc.date.available 2021-02-09T04:31:29Z
dc.date.issued 2020-04 es_ES
dc.identifier.issn 0960-0779 es_ES
dc.identifier.uri http://hdl.handle.net/10251/160894
dc.description.abstract [EN] This paper concerns the computation of the probability density function of the stochastic solution to general complex systems with uncertainties formulated via random differential equations. In the existing literature, the uncertainty quantification for random differential equations is based on the approximation of statistical moments by simulation or spectral methods, or on the computation of the exact density function via the random variable transformation (RVT) method when a closed-form solution is available. However, the problem of approximating the density function in a general setting has not been published yet. In this paper, we propose a hybrid method based on stochastic polynomial expansions, the RVT technique, and multidimensional integration schemes, to obtain accurate approximations to the solution density function. A problem-independent algorithm is proposed. The algorithm is tested on the SIR (susceptible-infected-recovered) epidemiological model, showing significant improvements compared to the previous literature. es_ES
dc.description.sponsorship This work has been supported by the Spanish Ministerio de Economia y Competitividad grant MTM2017-89664-P. The author Marc Jornet acknowledges the doctorate scholarship granted by Programa de Ayudas de Investigacion y Desarrollo (PAID), Universitat Politecnica de Valencia. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Chaos, Solitons and Fractals es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Complex model with uncertainties es_ES
dc.subject Random differential equation es_ES
dc.subject Probability density function es_ES
dc.subject Stochastic polynomial expansion es_ES
dc.subject RVT technique es_ES
dc.subject SIR epidemic model es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Computing the density function of complex models with randomness by using polynomial expansions and the RVT technique. Application to the SIR epidemic model es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.chaos.2020.109639 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Calatayud, J.; Cortés, J.; Jornet, M. (2020). Computing the density function of complex models with randomness by using polynomial expansions and the RVT technique. Application to the SIR epidemic model. Chaos, Solitons and Fractals. 133:1-10. https://doi.org/10.1016/j.chaos.2020.109639 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.chaos.2020.109639 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 10 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 133 es_ES
dc.relation.pasarela S\400923 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
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