A Stochastic Schumacher Diffusion Process: Probability Characteristics Computation and Statistical Analysis

Ahmed Nafidi (), Abdenbi El Azri () and Ramón Gutiérrez-Sánchez ()
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Ahmed Nafidi: Hassan First University of Settat, National School of Applied Sciences
Abdenbi El Azri: Hassan First University of Settat, National School of Applied Sciences
Ramón Gutiérrez-Sánchez: University of Granada

Methodology and Computing in Applied Probability, 2023, vol. 25, issue 2, 1-15

Abstract: Abstract The principal goal of this article is to establish a methodological approach to computational statistical analysis for a new in-homogeneous stochastic diffusion process with mean function corresponds to the Schumacher curve. Firstly, we analyse the principal probabilistic characteristics like the functions of the mean and the transition probability density of the process. So, the parameters estimation appearing in the current process are determined by the maximum likelihood approach with discrete sampling. Finally, so as to provide the performance of the proposed process, we will apply these computational statistical results to simulated data based on a discretization of the analytical expression of the process by justifying the fit and prediction possibilities.

Keywords: Schumacher growth curve; Stochastic diffusion process; Statistical estimation; Goodness of fits; Computational simulation; Prediction; 62M86; 60H30; 65C30 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11009-023-10031-4

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