Dakota 6.3

Released: November 16, 2015
Release Highlights:

  • Numerous algorithmic and usability enhancements to Bayesian calibration capabilities.
  • Gaussian process models now exportable in human-readable format.
  • Incremental LHS now works for all discrete variable types including histograms and discrete sets. Support for string variables was also extended to the JEGA, COLIN, and NOMAD optimizers.
  • Updated training materials made available in the Community->Training section of the Dakota website.
  • Improvements in computation and consistency of reporting of PDFs and CDFs across UQ methods.
  • New interface keyword ‘labeled’ enables more rigorous results file validation and error reporting.