Bayesian Statistics Seminar
North Carolina State University
presents
Lovely Goyal
North Carolina State University
"Bayesian Inference for Nonlinear Mixed Effects Models involving Ordinary Differential Equations"
ABSTRACT
In the context of nonlinear mixed effect modeling, within subject mechanisms are often represented by a system of nonlinear ordinary differential equations (ODE) whose parameters characterize the different characteristics of the underlying population. These models are useful because they offer a flexible framework where parameters for both individuals and population can be estimated by combining information across all subjects. Estimating parameters for these models becomes challenging in the absence of any analytical solution for the system of ODE, involved in the modeling. We present a Bayesian Euler's Approximation Method (BEAM) that combines the existing Bayesian framework for estimation with the Euler's numerical approximation method, thereby providing an analytic closed form approximation for the ODE system. For illustration purposes, here we present the estimation results from an application of the proposed method to an HIV model.
Tuesday, September, 13, 2005
4:00 - 5:00 pm
208 Patterson Hall