Dear @Mr121Tony ,
if you are interested in making predictions in a “real case”, you have to generate a BayesOpts object as described in Section 3.1 of the manual describing the “real case” 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