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Bayesian inversion for a fractional Lotka-Volterra model: An application of Canadian lynx vs. snowshoe hares

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  • Ariza-Hernandez, Francisco J.
  • Martin-Alvarez, Luis M.
  • Arciga-Alejandre, Martin P.
  • Sanchez-Ortiz, Jorge

Abstract

The Bayesian statistical inversion method is implemented to obtain the parameter estimations for fractional LotkaVolterra models, including the derivative orders, based on analytical solutions obtained by the multi-step homotopy method. For the posterior distributions of the parameter of interest, we used Markov Chain Monte Carlo method through the JAGS package within R software. The posterior predictive model–checking method is implemented to select the best model for a real data set.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:151:y:2021:i:c:s0960077921006329
    DOI: 10.1016/j.chaos.2021.111278
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    References listed on IDEAS

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    1. 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.
    2. Baleanu, D. & Shiri, B., 2018. "Collocation methods for fractional differential equations involving non-singular kernel," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 136-145.
    3. Kumar, Sunil & Kumar, Ranbir & Cattani, Carlo & Samet, Bessem, 2020. "Chaotic behaviour of fractional predator-prey dynamical system," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    4. Alijani, Zahra & Baleanu, Dumitru & Shiri, Babak & Wu, Guo-Cheng, 2020. "Spline collocation methods for systems of fuzzy fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    5. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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