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Bayesian Analysis for a Fractional Population Growth Model

Author

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  • Francisco J. Ariza-Hernandez
  • Jorge Sanchez-Ortiz
  • Martin P. Arciga-Alejandre
  • Luis X. Vivas-Cruz

Abstract

We implement the Bayesian statistical inversion theory to obtain the solution for an inverse problem of growth data, using a fractional population growth model. We estimate the parameters in the model and we make a comparison between this model and an exponential one, based on an approximation of Bayes factor. A simulation study is carried out to show the performance of the estimators and the Bayes factor. Finally, we present a real data example to illustrate the effectiveness of the method proposed here and the pertinence of using a fractional model.

Suggested Citation

  • Francisco J. Ariza-Hernandez & Jorge Sanchez-Ortiz & Martin P. Arciga-Alejandre & Luis X. Vivas-Cruz, 2017. "Bayesian Analysis for a Fractional Population Growth Model," Journal of Applied Mathematics, Hindawi, vol. 2017, pages 1-9, January.
    • Handle: RePEc:hin:jnljam:9654506
    DOI: 10.1155/2017/9654506
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    Cited by:

    1. Francisco J. Ariza-Hernandez & Martin P. Arciga-Alejandre & Jorge Sanchez-Ortiz & Alberto Fleitas-Imbert, 2020. "Bayesian Derivative Order Estimation for a Fractional Logistic Model," Mathematics, MDPI, vol. 8(1), pages 1-9, January.
    2. Ariza-Hernandez, Francisco J. & Martin-Alvarez, Luis M. & Arciga-Alejandre, Martin P. & Sanchez-Ortiz, Jorge, 2021. "Bayesian inversion for a fractional Lotka-Volterra model: An application of Canadian lynx vs. snowshoe hares," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).

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