solver_metric

Metric employed during numerical solutions in sampling-based multifidelity UQ methods.

Specification

• Alias: None

• Arguments: None

• Default: average_estimator_variance

Child Keywords:

Required/Optional	Description of Group	Dakota Keyword	Dakota Keyword Description
Required (Choose One)	Optimization Solver Metric	average_estimator_variance	Utilize the estimator variance averaged over the QoI as the solver metric for sampling-based multifidelity methods.
		norm_estimator_variance	Utilize a p-norm over the vector of QoI estimator variances as the solver metric for sampling-based multifidelity methods.
		max_estimator_variance	Utilize the maximum estimator variance as the solver metric for sampling-based multifidelity methods.

Description

For sampling-based multifidelity UQ methods, this specification selects the metric to be used during numerical solutions for sample allocations per model. When there are multiple quantities of interest (QoI), the vector of QoI estimator variances needs to be converted to a scalar for use by the numerical solver. Options include the average, maximum, and p-norm of the QoI vector, with the default of average estimator variance.

Examples

method,
    approximate_control_variate acv_mf
      solver_metric norm_estimator_variance norm_order = 2  # objective fn for budget-constrained
    solution_mode  online_pilot
    pilot_samples = 50 seed = 8674132
    max_function_evaluations = 500