Sensitivity Analysis for Uncertainty Quantification in Mathematical Models

Leon Arriola () and James M. Hyman ()
Additional contact information
Leon Arriola: University of Wisconsin–Whitewater, Department of Mathematical and Computer Sciences
James M. Hyman: Los Alamos National Laboratory, Theoretical Division, MS B284

A chapter in Mathematical and Statistical Estimation Approaches in Epidemiology, 2009, pp 195-247 from Springer

Abstract: Abstract All mathematical models are approximate and their usefulness depends on our understanding the uncertainty inherent in the predictions. Uncertainties can affect the reliability of the results at every stage of computation; they may grow or even shrink as the solution of the model evolves. Often these inherent uncertainties cannot be made arbitrarily small by a more complex model or additional computation and we must understand how the uncertainty in the model parameters, the initial conditions, and the model itself, lead to uncertainties in the model predictions. This chapter is an introductory survey of sensitivity analysis and illustrates how to define the derivative of the model solution as a function of the model input and determine the relative importance of the model parameters on the model predictions.

Keywords: Linear Programming Problem; Sensitivity Index; Singular Vector; Initial Value Problem; Algorithmic Differentiation (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-90-481-2313-1_10

Ordering information: This item can be ordered from
http://www.springer.com/9789048123131

DOI: 10.1007/978-90-481-2313-1_10

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().