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Sensitivities

Which variable appears to be the most important?

The significance of a variable for a response can be illustrated with ANOVA (analysis of variance) or GSA/Sobol (global sensitivity analysis), e.g for the response HIC you may find:

New Plot

  • To view a new plot select the plot button on the task bar. A seperate window of LS-OPT Viewer opens up.

LS-OPT Viewer

    ANOVA

  1. Select under Metamodel select the item Sensitivity
  2. Select  Linear ANOVA in the new window.
  3. From Response select HIC.
  4. Sort the variables according to their significance for HIC.

 new viewer

mainscreen_sensitivity

→ In this case the confidence intervals for both variables thood and tbumber are so wide (especially for tbumber) that one cannot end up with a conclusion about their linear significancies for the response HIC

sen_1

    GSA/Sobol
  1. Select GSA/Sobol.
  2. From Response select HIC.
  3. Sort the variables according to their significance for HIC.

 

→ We come to the same conclusion by using GSA. The influence of thood on HIC is 84.9%, larger than that of tbumper (15.1%).

GSA is a non-linear sensitivity measure, but evaluated on the metamodel, which is linear here. Hence it should lead to the same ranking than ANOVA.

sen_2