this is my very first post on this community, so I would like to say thank you for the project. I am Michele Capriati, PhD candidate and I am currently using UQLab for my study.
I am building a hierarchical Kriging following ‘The Gaussian process modelling module in UQLab’ article, anyway I come across a problem when applying it to my case study.
When I build the multi fidelity using the original uncertainty input space, the model response is good on the training points, but it seems to do not change the trend on the rest of the space, as in the following figure:
(legend: f:real function, LF:low fidelity model on 80 points, HF: High fidelity model on 3 points, MF: Multi-Fidelity on the same 3 points )
Anyway I noticed that normalizing the space, leads to much better results (I cannot post more than one picture.)
I would like to ask if such a problem was already been reported, or it is most likely due to a mistake in my script.
Many thanks, Michele