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