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Title: Parameter estimation for a glucose/Insulin nonlinear differential equation model by using MCMC and GLS methods
Authors: Yongwimon Lenbury
Keywords: MCMC;GLS
Issue Date: 2012
Publisher: The 17th Annunal Meeting in Mathematics
Citation: คณิตศาสตร์
Abstract: In this study, we estimate the parameters in a glucose/insulin nonlinear differential model with GLP1-DPP4 interaction, describing the role of the Glucagon-like peptide-1 and dipeptidyl-peptidase-4 on the glucose/insulin metabolism, by using the Markov Chain Monte Carlo (MCMC) method, which is used in a Bayesian setting, and Generalized Least Square (GLS) method, which is used in the classical statistic formulation. A comparison between the two methods are performed in terms of point and interval parameter estimates. Our results show that MCMC is capable to estimate the parameters in this model based on smaller bias and standard deviation.
Appears in Collections:Mathematics: International Proceedings

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