Package

dakota

Description

The Dakota toolkit provides a flexible, extensible interface between
analysis codes and iterative systems analysis methods. Dakota contains
algorithms for: - optimization with gradient and non gradient-based
methods; - uncertainty quantification with sampling, reliability,
stochastic - expansion, and epistemic methods; - parameter estimation
with nonlinear least squares methods; - sensitivity/variance analysis
with design of experiments and - parameter study methods. These
capabilities may be used on their own or as components within advanced
strategies such as hybrid optimization, surrogate-based optimization,
mixed integer nonlinear programming, or optimization under uncertainty.

Note