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Functional sensitivity analysis of mathematical models

Authors: DH Martin;

Functional sensitivity analysis of mathematical models

Abstract

When real dynamical systems or processes are modelled using ordinary differential equations, the question arises of gauging the sensitivity of predictions derived from the model to possible perturbations in various uncertain or assumed expressions or functions which appear in the differential equations. Often, for example, various terms will be assumed to be linear, and sensitivity analysis should then study not only the effects of perturbing the constant of proportionality (parameter sensitivity analysis) but also the effect of abandoning the assumption of linearity (functional sensitivity analysis).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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