On the Parameters Estimation of HIV Dynamic Models
DOI:
https://doi.org/10.57805/revstat.v17i2.265Keywords:
parameter estimation, nonlinear programming, mathematical models, human immunodeficiency virus (HIV)Abstract
This work proposes an estimation method to obtain the optimal parameter estimates of a mathematical model, from a set of CD4+T values collected in a HIV patient. To this end, the following scheme is adopted: the first step consists in selecting an initial estimate for the model’s parameters as that having minimum square error, from a set of uniform randomly generated candidates. In the second step, the initial solution is refined by an optimization algorithm with constraints and bounds (imposed by physiology), resulting on the optimal estimate. The proposed method is validated through a simulation study and illustrated with an application to a real data set of CD4+T cells counts for several HIV patients.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 REVSTAT-Statistical Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.