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A note on the logistic equation subject to uncertainties in parameters

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Abstract

This paper discusses the logistic equation subject to uncertainties in the intrinsic growth rate, \(\alpha \), in the initial population density, \(N_0\), and in the environmental carrying capacity, K. These parameters are treated as independent random variables. The random variable transformation method is applied to compute the first probability density function of the time–population density, N(t), and of its inflection point, \(t^{*}\). Results for the density functions of N(t), for a fixed \(t>0\), and \(t^{*}\) are also provided for \(\alpha \), \(N_0\) and K uniformly distributed. Finally, numerical experiments illustrate the proposed theoretical results.

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References

  • Casabán MC, Cortés JC, Romero JV, Roselló MD (2015) Probabilistic solution of random SI-type epidemiological models using the random variable transformation technique. Commun Nonlinear Sci Numer Simul 24:86–97

    Article  MathSciNet  Google Scholar 

  • Casabán MC, Cortés JC, Navarro-Quiles A, Romero JV, Roselló MD, Villanueva RJ (2016) A comprehensive probabilistic solution of random SIS-type epidemiological models using the random variable transformation technique. Commun Nonlinear Sci Numer Simul 32:199–210

    Article  MathSciNet  Google Scholar 

  • Dorini FA, Cecconello MS, Dorini LB (2016) On the logistic equation subject to uncertainties in the environmental carrying capacity and initial population density. Commun Nonlinear Sci Numer Simul 33:160–173

    Article  MathSciNet  Google Scholar 

  • Henderson D, Plaschko P (2006) Stochastic differential equations in science and engineering. World Scientific, Singapore

    Book  MATH  Google Scholar 

  • Holland EP, Burrow JF, Dytham C, Aegerter JN (2009) Modelling with uncertainty: introducing a probabilistic framework to predict animal population dynamics. Ecol Model 220:1203–1217

    Article  Google Scholar 

  • Kegan B, West RW (2005) Modeling the simple epidemic with deterministic differential equations and random initial conditions. Math Biosci 195:179–193

    Article  MathSciNet  MATH  Google Scholar 

  • Kot M (2001) Elements of mathematical ecology. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Lek S (2007) Uncertainty in ecological models. Ecol Model 207:1–2

    Article  Google Scholar 

  • Nasell I (2003) Moment closure and the stochastic logistic model. Theor Popul Biol 63:159–168

    Article  Google Scholar 

  • Soong TT (1973) Random differential equations in science and engineering. Academic Press, New York

    MATH  Google Scholar 

  • Udwadia FE (1989) Some results on maximum entropy distributions for parameters known to lie in finite intervals. SIAM Rev 31:103–109

    Article  MathSciNet  MATH  Google Scholar 

  • Wake GC, Watt SD (1996) The relaxation of May’s conjecture for the logistic equation. Appl Math Lett 9:59–62

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

First author acknowledges the financial support from the Brazilian Council for Development of Science and Technology-CNPq (Grants Numbers 308149/2013-0 and 482320/2013-3).

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Correspondence to Fabio A. Dorini.

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Communicated by Jose Alberto Cuminato.

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Dorini, F.A., Bobko, N. & Dorini, L.B. A note on the logistic equation subject to uncertainties in parameters. Comp. Appl. Math. 37, 1496–1506 (2018). https://doi.org/10.1007/s40314-016-0409-6

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  • DOI: https://doi.org/10.1007/s40314-016-0409-6

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