- -

Improving the approximation of the probability density function of random nonautonomous logistic-type differential equations

RiuNet: Institutional repository of the Polithecnic University of Valencia

Share/Send to

Cited by

Statistics

  • Estadisticas de Uso

Improving the approximation of the probability density function of random nonautonomous logistic-type differential equations

Show full item record

Calatayud-Gregori, J.; Cortés, J.; Jornet-Sanz, M. (2019). Improving the approximation of the probability density function of random nonautonomous logistic-type differential equations. Mathematical Methods in the Applied Sciences. 42(18):7259-7267. https://doi.org/10.1002/mma.5834

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/144799

Files in this item

Item Metadata

Title: Improving the approximation of the probability density function of random nonautonomous logistic-type differential equations
Author: Calatayud-Gregori, Julia Cortés, J.-C. Jornet-Sanz, Marc
UPV Unit: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Issued date:
Abstract:
[EN] In this paper, we address the problem of approximating the probability density function of the following random logistic differential equation: P-'(t,omega)=A(t,omega)(1-P(t,omega))P(t,omega), t is an element of[t(0),T], ...[+]
Subjects: Mean square expansion , Probability density function , Random logistic differential equation
Copyrigths: Cerrado
Source:
Mathematical Methods in the Applied Sciences. (issn: 0170-4214 )
DOI: 10.1002/mma.5834
Publisher:
John Wiley & Sons
Publisher version: https://doi.org/10.1002/mma.5834
Project ID:
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/
Thanks:
Secretaria de Estado de Investigacion, Desarrollo e Innovacion, Grant/Award Number: MTM2017-89664-P; Universitat Politecnica de Valencia, Grant/Award Number: Programa de Ayudas de Investigacion y Desarrollo
Type: Artículo

References

Cortés, J.-C., Navarro-Quiles, A., Romero, J.-V., & Roselló, M.-D. (2019). Analysis of random non-autonomous logistic-type differential equations via the Karhunen–Loève expansion and the Random Variable Transformation technique. Communications in Nonlinear Science and Numerical Simulation, 72, 121-138. doi:10.1016/j.cnsns.2018.12.013

Strand, J. . (1970). Random ordinary differential equations. Journal of Differential Equations, 7(3), 538-553. doi:10.1016/0022-0396(70)90100-2

Bharucha-Reid, A. T. (1964). On the theory of random equations. Proceedings of Symposia in Applied Mathematics, 40-69. doi:10.1090/psapm/016/0189071 [+]
Cortés, J.-C., Navarro-Quiles, A., Romero, J.-V., & Roselló, M.-D. (2019). Analysis of random non-autonomous logistic-type differential equations via the Karhunen–Loève expansion and the Random Variable Transformation technique. Communications in Nonlinear Science and Numerical Simulation, 72, 121-138. doi:10.1016/j.cnsns.2018.12.013

Strand, J. . (1970). Random ordinary differential equations. Journal of Differential Equations, 7(3), 538-553. doi:10.1016/0022-0396(70)90100-2

Bharucha-Reid, A. T. (1964). On the theory of random equations. Proceedings of Symposia in Applied Mathematics, 40-69. doi:10.1090/psapm/016/0189071

Neckel, T., & Rupp, F. (2013). Random Differential Equations in Scientific Computing. doi:10.2478/9788376560267

Murray, J. D. (Ed.). (2002). Mathematical Biology. Interdisciplinary Applied Mathematics. doi:10.1007/b98868

Licea, J. A., Villafuerte, L., & Chen-Charpentier, B. M. (2013). Analytic and numerical solutions of a Riccati differential equation with random coefficients. Journal of Computational and Applied Mathematics, 239, 208-219. doi:10.1016/j.cam.2012.09.040

Dorini, F. A., Cecconello, M. S., & Dorini, L. B. (2016). On the logistic equation subject to uncertainties in the environmental carrying capacity and initial population density. Communications in Nonlinear Science and Numerical Simulation, 33, 160-173. doi:10.1016/j.cnsns.2015.09.009

Dorini, F. A., Bobko, N., & Dorini, L. B. (2016). A note on the logistic equation subject to uncertainties in parameters. Computational and Applied Mathematics, 37(2), 1496-1506. doi:10.1007/s40314-016-0409-6

Cortés, J.-C., Navarro-Quiles, A., Romero, J.-V., & Roselló, M.-D. (2018). Computing the probability density function of non-autonomous first-order linear homogeneous differential equations with uncertainty. Journal of Computational and Applied Mathematics, 337, 190-208. doi:10.1016/j.cam.2018.01.015

Burgos, C., Calatayud, J., Cortés, J.-C., & Navarro-Quiles, A. (2018). A full probabilistic solution of the random linear fractional differential equation via the random variable transformation technique. Mathematical Methods in the Applied Sciences, 41(18), 9037-9047. doi:10.1002/mma.4881

Lord, G. J., Powell, C. E., & Shardlow, T. (2009). An Introduction to Computational Stochastic PDEs. doi:10.1017/cbo9781139017329

CalatayudJ CortésJC JornetM. On the approximation of the probability density function of the randomized non‐autonomous complete linear differential equation. arXiv preprint arXiv:1802.04188;2018.

Calatayud, J., Cortés, J.-C., & Jornet, M. (2018). The damped pendulum random differential equation: A comprehensive stochastic analysis via the computation of the probability density function. Physica A: Statistical Mechanics and its Applications, 512, 261-279. doi:10.1016/j.physa.2018.08.024

Vaart, A. W. van der. (1998). Asymptotic Statistics. doi:10.1017/cbo9780511802256

Wolfram Research Inc. Mathematica. Version 11.2 Champaign Illinois;2017.

[-]

recommendations

 

This item appears in the following Collection(s)

Show full item record