Statistical inference for non-linear models involving ordinary differential equations

DOI10.1080/15598608.2010.10412015zbMath1420.62077OpenAlexW2019079489MaRDI QIDQ2324138

Lovely Goyal, Sujit Kumar Ghosh

Publication date: 13 September 2019

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2010.10412015

zbMATH Keywords

splinesordinary differential equationsBayesian inferenceMCMCnon-linear models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Parametric hypothesis testing (62F03) Bayesian inference (62F15)

Cites Work

• Relationships between antiviral treatment effects and biphasic viral decay rates in modeling HIV dynamics
• The Bayesian Analysis of Population Pharmacokinetic Models
• Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions
• Reference Bayesian Methods for Generalized Linear Mixed Models
• Numerical Solution of Ordinary Differential Equations
• Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
• Monte Carlo sampling methods using Markov chains and their applications
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