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Probabilistic analysis of linear-quadratic logistic-type models with hybrid uncertainties via probability density functions

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Probabilistic analysis of linear-quadratic logistic-type models with hybrid uncertainties via probability density functions

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dc.contributor.author Burgos-Simon, Clara es_ES
dc.contributor.author Cortés, J.-C. es_ES
dc.contributor.author López-Navarro, Elena es_ES
dc.contributor.author Villanueva Micó, Rafael Jacinto es_ES
dc.date.accessioned 2022-02-04T19:03:38Z
dc.date.available 2022-02-04T19:03:38Z
dc.date.issued 2021-03-02 es_ES
dc.identifier.uri http://hdl.handle.net/10251/180500
dc.description.abstract [EN] We provide a full stochastic description, via the first probability density function, of the solution of linear-quadratic logistic-type differential equation whose parameters involve both continuous and discrete random variables with arbitrary distributions. For the sake of generality, the initial condition is assumed to be a random variable too. We use the Dirac delta function to unify the treatment of hybrid (discrete-continuous) uncertainty. Under general hypotheses, we also compute the density of time until a certain value (usually representing the population) of the linear-quadratic logistic model is reached. The theoretical results are illustrated by means of several examples, including an application to modelling the number of users of Spotify using real data. We apply the Principle Maximum Entropy to assign plausible distributions to model parameters es_ES
dc.description.sponsorship This work has been supported by the Spanish Ministerio de Economa, Industria y Competitividad (MINECO) , the Agencia Estatal de Investigaci on (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM201789664P. Computations have been carried thanks to the collaboration of Raul San Julian Garces and Elena Lopez Navarro granted by European Union through the Operational Program of the European Regional Development Fund (ERDF) /European Social Fund (ESF) of the Valencian Community 2014-2020, grants GJIDI/2018/A/009 and GJIDI/2018/A/010, respectively es_ES
dc.language Inglés es_ES
dc.publisher American Institute of Mathematical Sciences es_ES
dc.relation.ispartof AIMS Mathematics es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Hybrid uncertainty es_ES
dc.subject Random linear-quadratic logistic differential equation es_ES
dc.subject First probability density function es_ES
dc.subject Random variable transformation method es_ES
dc.subject Uncertainty quantification es_ES
dc.subject Principle Maximum Entropy es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Probabilistic analysis of linear-quadratic logistic-type models with hybrid uncertainties via probability density functions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3934/math.2021290 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.relation.projectID info:eu-repo/grantAgreement/EDUC.INVEST.CULT.DEP//GJIDI%2F2018%2FA%2F009//AYUDA GARANTIA JUVENIL GVA-ACTUALIZACIÓN DE UN SISTEMA CLIENTE-SERVIDOR DE COMPUTACIÓN DISTRIBUIDA/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EDUC.INVEST.CULT.DEP//GJIDI%2F2018%2FA%2F010//AYUDA GARANTIA JUVENIL GVA: PERSONAL TECNICO-GESTOR EN MODELIZACION MATEMATICA/ 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.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària es_ES
dc.description.bibliographicCitation Burgos-Simon, C.; Cortés, J.; López-Navarro, E.; Villanueva Micó, RJ. (2021). Probabilistic analysis of linear-quadratic logistic-type models with hybrid uncertainties via probability density functions. AIMS Mathematics. 6(5):4938-4957. https://doi.org/10.3934/math.2021290 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3934/math.2021290 es_ES
dc.description.upvformatpinicio 4938 es_ES
dc.description.upvformatpfin 4957 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 6 es_ES
dc.description.issue 5 es_ES
dc.identifier.eissn 2473-6988 es_ES
dc.relation.pasarela S\429825 es_ES
dc.contributor.funder GENERALITAT VALENCIANA es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder European Regional Development Fund es_ES
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