- -

Solving the Random Pielou Logistic Equation with the Random Variable Transformation Technique: Theory and Applications

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Solving the Random Pielou Logistic Equation with the Random Variable Transformation Technique: Theory and Applications

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Cortés, J.-C. es_ES
dc.contributor.author Navarro-Quiles, A. es_ES
dc.contributor.author Romero, José-Vicente es_ES
dc.contributor.author Roselló, María-Dolores es_ES
dc.date.accessioned 2020-03-31T06:46:20Z
dc.date.available 2020-03-31T06:46:20Z
dc.date.issued 2019-11-30 es_ES
dc.identifier.issn 0170-4214 es_ES
dc.identifier.uri http://hdl.handle.net/10251/139845
dc.description.abstract [EN] The study of the dynamics of the size of a population via mathematical modelling is a problem of interest and widely studied. Traditionally, continuous deterministic methods based on differential equations have been used to deal with this problem. However, discrete versions of some models are also available and sometimes more adequate. In this paper, we randomize the Pielou logistic equation in order to include the inherent uncertainty in modelling. Taking advantage of the method of transformation of random variables, we provide a full probabilistic description to the randomized Pielou logistic model via the computation of the probability density functions of the solution stochastic process, the steady state, and the time until a certain level of population is reached. The theoretical results are illustrated by means of two examples: The first one consists of a numerical experiment and the second one shows an application to study the diffusion of a technology using real data. es_ES
dc.description.sponsorship This work has been partially supported by the Ministerio de Economía y Competitividad grant MTM2017-89664-P es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Mathematical Methods in the Applied Sciences es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject First probability density function es_ES
dc.subject Modelling real data es_ES
dc.subject Pielou logistic equation es_ES
dc.subject Population dynamics es_ES
dc.subject Random difference stochastic equations es_ES
dc.subject Random variable transformation technique es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Solving the Random Pielou Logistic Equation with the Random Variable Transformation Technique: Theory and Applications es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/mma.5440 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 Cortés, J.; Navarro-Quiles, A.; Romero, J.; Roselló, M. (2019). Solving the Random Pielou Logistic Equation with the Random Variable Transformation Technique: Theory and Applications. Mathematical Methods in the Applied Sciences. 42(17):5708-5717. https://doi.org/10.1002/mma.5440 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/mma.5440 es_ES
dc.description.upvformatpinicio 5708 es_ES
dc.description.upvformatpfin 5717 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 42 es_ES
dc.description.issue 17 es_ES
dc.relation.pasarela S\376560 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.description.references Kwasnicki, W. (2013). Logistic growth of the global economy and competitiveness of nations. Technological Forecasting and Social Change, 80(1), 50-76. doi:10.1016/j.techfore.2012.07.007 es_ES
dc.description.references Chen-Charpentier, B. M., & Stanescu, D. (2011). Biofilm growth on medical implants with randomness. Mathematical and Computer Modelling, 54(7-8), 1682-1686. doi:10.1016/j.mcm.2010.11.075 es_ES
dc.description.references Wolfram Research Inc.Mathematica. Version 11.2 Champaign IL;2018. es_ES
dc.description.references CNMC Comisión Nacional de los Mercados y la Competencia.http://data.cnmc.es/datagraph/jsp/inf_anual.jsp Accessed: 2018‐07‐24 (in Spanish). es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem