Parameter Selection Methods in Inverse Problem Formulation
Quantitative Methods
2020-04-20 v1 Populations and Evolution
Abstract
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.
Cite
@article{arxiv.2004.07821,
title = {Parameter Selection Methods in Inverse Problem Formulation},
author = {H. T. Banks and Ariel Cintrón-Arias},
journal= {arXiv preprint arXiv:2004.07821},
year = {2020}
}