Looking for documentation/example of using UQLab results of Bayesian inference for forward UQ or further Bayesian inference

UQ with UQLab Community Q&A and How To
2

Hi Olaf

There is currently no example that explains this - but using the .Results.PostProc.PostSample is the correct starting point. There are a couple of things you can do with this sample, but first of all, you will have to transform it to a 2D array with

PostSample2D = reshape(permute(PostSample3D, [2 1 3]), size(PostSample3D, 2), []).'

You could then, of course, directly propagate this sample through a different forward model, but to use advanced UQ methods (or for another round of inference where this posterior measure is used as a prior measure), you will have to find a parametric distribution that can be used to represent this sample.

For this, I suggest you have a look at the new input module that was released in v.1.3 of UQLab. More specifically, have a look at the inference of marginals and copulas as detailed in this example. This will allow you to define a new uq_input object using the posterior sample. This object can then be used to do any UQ analysis you desire.

Let me know how it goes!

3 Likes