Probabilistic Methods for Addressing Uncertainty and Variability in Biological Models: Application to a Toxicokinetic Model
Abstract
Population variability and uncertainty are important features of biological systems that must be considered when developing mathematical models for these systems. In this paper we present probability-based parameter estimation methods that account for such variability and uncertainty. Theoretical results that establish well-posedness and stability for these methods are discussed. A probabilistic parameter estimation technique is then applied to a toxicokinetic model for trichloroethylene using several types of simulated data. Comparison with results obtained using a standard, deterministic parameter estimation method suggests that the probabilistic methods are better able to capture population variability and uncertainty in model parameters. Key words: Parameter estimation, biological modeling, population variability, model uncertainty, toxicokinetics, trichloroethylene
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 13, 2002
- Accession Number
- ADA453196
Entities
People
- H. Thomas Banks
- Laura K. Potter
Organizations
- North Carolina State University