Hi there,

We are including UQLab in a Civil Engineering FEM Software (ZSoil).

Our workflow is to:

- define marginals of the input
- define copula
- get a sample of the input
- evaluate this sample in ZSoil
- define an output
- generate a metamodel on this experimental design (PCE, PCK or Kriging)
- sensitivity analysis
- reliability analysis
- bayesian analysis

When using high correlation coefficients in the copula, we encountered issues in the Bayesian analysis. We circumvented this issue by generating the experimental design on an uncorrelated sample.

This lead to a more general question: **How does the accuracy of the metamodel change, if the copula is ignored for the generation of the experimental design?**

Some thoughts, we had on this topic:

- The metamodel might be less prone to overfitting, because the examples are more “different”
- The accuracy in more unlikely regions of the random vector space might be better (as shown in this UQ World Post: Choice of distribution for the construction of a meta-model)
- The overall accuracy might be slightly worse, because information on the samples is omitted

Thanks!