Hi @mercya,

Welcome to UQWorld !

Figure 8 is based on Kriging predictor of Eqs. (1.6) and (1.7) in the Kriging User Manual. The plot represents Gaussian random variables at some input points (\mathbf{x}) conditioned on the observed data (the black filled circles you see in the plot). To compute both equations, it is assumed that we already know everything about the Kriging model:

- the trend basis functions (\mathbf{f})
- the corresponding coefficients of the trend function \mathbf{\beta}
- the correlation function R
- the corresponding parameters of the correlation function (\mathbf{\theta})
- the process variance \sigma^2
- the observed points \mathcal{X} and \mathcal{Y}

Referring to Figure 8, the solid blue line and shaded gray area represent the mean of the Kriging predictor (Eq. (1.6)) and twice (well, 1.96) the standard deviation around the mean (Eq. (1.7)), respectively. It is plotted for 500 uniformly spaced points in the domain of the input. I think what’s displayed on `uq_print`

should be enough to reproduce the plot.

`uq_display`

function is an entry point for all the default display functions of UQLab objects (MODEL, ANALYSIS, INPUT). In the case of Kriging MODEL object, `uq_display`

function actually runs `uq_Kriging_display`

.

I hope this answers your question.