Abstract
Methodologies are presented for assessing the feasibility of parameter estimation in nonlinear ordinary differential equation (ODE) models. These methods are applied to a recent model for hepatitis C viral dynamics. Subset selection is performed on the model parameters, and maximum likelihood estimation is conducted using available data from the literature.