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dakota.csh | ||
dakota.info | ||
dakota.sh | ||
dakota.SlackBuild | ||
doinst.sh | ||
README | ||
slack-desc |
The Dakota toolkit provides a flexible, extensible interface between analysis codes and iteration methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, stochastic expansion, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study capabilities. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Optional dependency: openmpi