Dear Professors,

In addition to parameter calibration, can the Bayesian inference module in UQLab be used to make predictions?

best wishes

Student

Dear @Mr121Tony

It is not exactly clear to me what you mean by â€śmaking predictionâ€ť. Are you interested in the predictive distribution? If yes, I suggest you to first have a look at the manual:

Let us know if this is not what youâ€™re interested in or if you are stuck with the implementation.

Best regards

Styfen

In UQLab - Bayesian inversion user manual, there are model predictions as shown in the picture. How can I use it to make predictions in a real case?

Dear @Mr121Tony ,

if you are interested in making predictions in a â€śreal caseâ€ť, you have to generate a `BayesOpts`

object as described in Section 3.1 of the manual describing the â€śreal caseâ€ť and use this as input for `uq_createAnalysis`

. Using the `.Results.PostProc.PostSample`

-component of the struct resulting from this this function call one can compute predictions, which I prefer to denote as performing forward UQ.

Following the suggestion by Paul-Remo in https://uqworld.org/t/looking-for-documentation-example-of-using-uqlab-results-of-bayesian-inference-for-forward-uq-or-further-bayesian-inference/690/2?u=olaf.klein I extract 2D-arrays containing sample-vectors of

the values of the different parameters combined with a value for the computed discrepancy. Afterwards I use these sample-vectors to perform Forward UQ

similar to the method the posterior predictive samples are computed in UQLab:

for each sample-vector I computed the value for my model for the given set of

parameter values and afterwards noise was added by computing a noise sample

for a normal distributed error according to the corresponding discrepancy value to

get a sample for the posterior predictive density.

Greetings

Olaf