Dealing with variability in ecological modelling: An analysis of a random non-autonomous logistic population model
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Otros documentos de la autoría: Calatayud, Julia; Cortés, Juan Carlos; Dorini, Fabio Antonio; Jornet, Marc
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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Título
Dealing with variability in ecological modelling: An analysis of a random non-autonomous logistic population modelFecha de publicación
2021-05-09Editor
John Wiley & Sons, Ltd.ISSN
0170-4214; 1099-1476Cita bibliográfica
Calatayud, J., Cortés, J. C., Dorini, F. A., & Jornet, M. (2022). Dealing with variability in ecological modelling: An analysis of a random non‐autonomous logistic population model. Mathematical Methods in the Applied Sciences, 45(6), 3318-3333Tipo de documento
info:eu-repo/semantics/articleVersión
info:eu-repo/semantics/acceptedVersionPalabras clave / Materias
Resumen
This paper presents a methodology to deal with the randomness associated toecological modelling. Data variability makes it necessary to analyse the impactof random perturbations on the fitted model parameters. We ... [+]
This paper presents a methodology to deal with the randomness associated toecological modelling. Data variability makes it necessary to analyse the impactof random perturbations on the fitted model parameters. We conduct suchanalysis for the logistic growth model with a certain sigmoid functional formof the carrying capacity, which was proposed in the literature for the study ofparasite growth during infection. We show how the probability distributions ofthe parameters are set via the maximum entropy principle. Then the randomvariable transformation method allows for computing the density function ofthe population. [-]
Publicado en
Mathematical Methods in the Applied Sciences, Vol. 45, Iss. 6. Special Issue: Mathematical Modelling in Engineering & Human Behavior 2020 (April 2022)Entidad financiadora
Agencia Estatal de Investigación (AEI) | Ministerio de Economía y Competitividad
Código del proyecto o subvención
PID2020-115270GB-I00
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© 2021John Wiley & Sons, Ltd.
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