Numerical non-identifiability regions of the minimal model of glucose kinetics: Superiority of Bayesian estimation

DOI10.1016/S0025-5564(03)00044-0zbMath1016.62126WikidataQ44466565 ScholiaQ44466565MaRDI QIDQ1399012

Gianluigi Pillonetto, Claudio Cobelli, Sparacino, Giovanni

Publication date: 7 August 2003

Published in: Mathematical Biosciences (Search for Journal in Brave)

zbMATH Keywords

parameter estimationmaximum likelihood estimationMarkov chain Monte Carlodiabetesminimum variance estimateinsulin sensitivity

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Bayesian inference (62F15) Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) (92C45)

Related Items (7)

Modelling the effect of CSII on the control of glucose concentration in type 1 diabetes ⋮ Practical identifiability of parametrised models: a review of benefits and limitations of various approaches ⋮ A three-compartment model of the C-peptide-insulin dynamic during the DIST test ⋮ Transmission dynamics of the great influenza pandemic of 1918 in Geneva, Switzerland: assessing the effects of hypothetical interventions ⋮ The dimensional reduction method for identification of parameters that trade-off due to similar model roles ⋮ Mathematical models and software tools for the glucose\,-\,insulin regulatory system and diabetes: an overview ⋮ A methodical survey of mathematical model-based control techniques based on open and closed loop control approach for diabetes management

Uses Software

• BayesDA
• MINMOD
• Gibbsit

Cites Work

• Markov chains and stochastic stability
• Monte Carlo sampling methods using Markov chains and their applications
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