Dakota Reference Manual: epistemic_uncertainty_quantification_methods

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epistemic_uncertainty_quantification_methods

## Description

Epistemic uncertainty is uncertainty due to lack of knowledge.

In Dakota, epistemic uncertainty analysis is performed using interval analysis or Dempster-Shafer theory of evidence.

Note that epistemic uncertainty can also be modeled probabilistically. It would be more accurate to call this class of method, non-probabilistic uncertainty quantification, but the name persists for historical reasons.

## Related Topics

- interval_estimation
- evidence_theory

## Related Keywords

- global_evidence : Evidence theory with evidence measures computed with global optimization methods
- global_interval_est : Interval analysis using global optimization methods
- local_evidence : Evidence theory with evidence measures computed with local optimization methods
- local_interval_est : Interval analysis using local optimization