Dakota Reference Manual  Version 6.4
Large-Scale Engineering Optimization and Uncertainty Analysis
 All Pages
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

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