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<p>This paper considers two stochastic diffusion processes associated with a general growth curve that includes a wide family of growth phenomena. The resulting processes are lognormal and Gaussian, and for them inference is addressed by means of the maximum likelihood method. The complexity of the resulting system of equations requires the use of metaheuristic techniques. The limitation of the parameter space, typically required by all metaheuristic techniques, is also provided by means of a suitable strategy. Several simulation studies are performed to evaluate to goodness of the proposed methodology, and an application to real data is described.</p>

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Inference on diffusion processes related to a general growth model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月20日

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  • Giuseppina Albano,
  • Antonio Barrera,
  • Virginia Giorno,
  • Francisco Torres-Ruiz

摘要

This paper considers two stochastic diffusion processes associated with a general growth curve that includes a wide family of growth phenomena. The resulting processes are lognormal and Gaussian, and for them inference is addressed by means of the maximum likelihood method. The complexity of the resulting system of equations requires the use of metaheuristic techniques. The limitation of the parameter space, typically required by all metaheuristic techniques, is also provided by means of a suitable strategy. Several simulation studies are performed to evaluate to goodness of the proposed methodology, and an application to real data is described.