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Dakota  Version 6.2
Public Member Functions | Protected Member Functions | Private Attributes
NonDLocalSingleInterval Class Reference

Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification. More...

Inheritance diagram for NonDLocalSingleInterval:
NonDLocalInterval NonDInterval NonD Analyzer Iterator

List of all members.

Public Member Functions

 NonDLocalSingleInterval (ProblemDescDB &problem_db, Model &model)
 constructor
 ~NonDLocalSingleInterval ()
 destructor

Protected Member Functions

void initialize ()
 perform any required initialization
void post_process_cell_results (bool maximize)
 post-process a cell minimization/maximization result

Private Attributes

size_t statCntr
 counter for finalStatistics

Detailed Description

Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification.

The NonDLocalSingleInterval class supports local gradient-based optimization apporaches to determining interval bounds for epistemic UQ. The interval bounds may be on the entire function in the case of pure interval analysis (e.g. intervals on input = intervals on output), or the intervals may be on statistics of an "inner loop" aleatory analysis such as intervals on means, variances, or percentile levels.


The documentation for this class was generated from the following files: