I’ve extracted datasets from experiments and want to perform a sensitivity analysis using UQLab. However, I couldn’t find any documentation on how to directly apply sensitivity analysis to raw data. From what I’ve seen, UQLab typically requires defining a model (i.e., a function) and then evaluating that function to generate the necessary data.
Is there a way to perform sensitivity analysis in UQLab using existing datasets, without explicitly defining a function? Any advice or suggestions would be appreciated!
Dear @saeid_saberi,
You cannot directly apply Sobol’ sensitivity analysis to an existing dataset without an underlying model. However, you can construct a Polynomial Chaos Expansion (PCE) surrogate based on your experimental design and compute Sobol’ indices from the PCE (see PCE-based Sobol’ indices in the manual). This approach is especially handy when working with small datasets, as it typically gives better results than the MC-based approach.
Hope this helps!
Best regards,
Styfen
Dear Styfen,
Thank you for the information. Actually, I’ve used AI-based methods, but I’ll try PCE-based Sobol as well.
Best