We discuss methods for {\em a priori} selection of parameters to be estimated in inverse problem formulations (such as Maximum Likelihood, Ordinary and Generalized Least Squares) for dynamical systems with numerous state variables and an even larger number of parameters. We illustrate the ideas with an in-host model for HIV dynamics which has been successfully validated with clinical data and used for prediction.
CITATION STYLE
Banks, H. T., Cintrón-Arias, A., & Kappel, F. (2013). Parameter Selection Methods in Inverse Problem Formulation (pp. 43–73). https://doi.org/10.1007/978-3-642-32882-4_3
Mendeley helps you to discover research relevant for your work.