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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 (for distributed memory parallel
capabilities)

You can build with multiple jobs by setting the MAKEFLAGS environment
variable.

 Name                                                       Last modified      Size  
 Parent Directory                                                                -   
 README                                                     04-Jun-2022 00:55  807   
 Theory-6.15.0.pdf                                          04-Jun-2022 00:57  1.7M  
 Users-6.15.0.pdf                                           04-Jun-2022 00:57  4.0M  
 dakota-6.15.0-public-src-cli.tar.gz                        04-Jun-2022 00:57  120M  
 dakota.SlackBuild                                          30-Apr-2022 08:58  3.6K  
 dakota.csh                                                 04-Jun-2022 00:55  228   
 dakota.info                                                04-Jun-2022 00:55  742   
 dakota.sh                                                  04-Jun-2022 00:55  229   
 doinst.sh                                                  04-Jun-2022 00:55  646   
 html-ref-6.15.0.tar.gz                                     04-Jun-2022 00:57  2.9M  
 slack-desc                                                 04-Jun-2022 00:55  952   

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