Well-Posedness and Stability of the Stochastic OGTT Model
Paul Bekima

TL;DR
This paper extends a deterministic OGTT model by incorporating stochastic noise, establishing its well-posedness and stability, and explores parameter estimation via MLE, enhancing the model's realism and robustness.
Contribution
It introduces a stochastic version of the OGTT model, proves its well-posedness and stability, and develops a maximum likelihood estimation scheme for parameter inference.
Findings
Existence and uniqueness of a global positive solution
Stability analysis via invariant measure
Effective parameter estimation method
Abstract
Oral Glucose Tolerance Test (OGTT) is one of many way to produce data in the study of the diabetes dynamic. In a recent paper [1.]:\textit{ Estimating insulin sensitivity and -cell function from the oral glucose tolerance test: validation of a new insulin sensitivity and secretion (ISS) model, \textit{J. American Physiological Society },(2024)},Ha J., Chung S.T., and al. proposed a comprehensive OGTT model under the form of a dynamic system. But their model was fully deterministic. Yet, our natural environment interacts with noise; thus taking into account that inherent perturbation could potentially improve the model, which in turn could lead to a better estimation of the parameters of the system. The current paper endeavors to explore the OGTT model proposed by Ha and al. but this time with the addition of white noise perturbations to the system.\ The work is organized as…
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Taxonomy
TopicsReservoir Engineering and Simulation Methods
