Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach

• Published in: Computational statistics Vol. 39; no. 6; pp. 2975 - 3005
• Main Authors: Clairon, Quentin, Pasin, Chloé, Balelli, Irene, Thiébaut, Rodolphe, Prague, Mélanie
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2024; Springer Nature B.V
• Subjects: Accuracy; Approximation; Cost function; Differential equations; Economic Theory/Quantitative Economics/Mathematical Methods; Epidemiology; Initial conditions; Mathematics and Statistics; Maximum likelihood estimation; Maximum likelihood method; Nonlinear control; Optimal control; Ordinary differential equations; Original Paper; Parameter estimation; Parameter identification; Pharmacodynamics; Pharmacokinetics; Probability and Statistics in Computer Science; Probability Theory and Stochastic Processes; Statistics; Virology; Mechanistic models; Clinical trial analysis; Ordinary differential equations; Optimal control theory; Nonlinear mixed effects models; Dynamic population models

We present a method for parameter estimation for nonlinear mixed-effects models based on ordinary differential equations (NLME-ODEs). It aims to regularize the estimation problem in the presence of model misspecification and practical identifiability issues, while avoiding the need to know or estima...