Hi @elieso and sorry for the delay, I have not had time to browse the forum for a while.
If your Kriging model has output dimension 2, let’s say \boldsymbol{Y}(x) = (Y_1(x), Y_2(x))^T where x is the N_d-dimensional input, then \boldsymbol{Y}(x) follows a bivariate normal distribution.
Therefore your conditional distribution is going to be defined with:
conditional = ot.Normal(2)
And your link function will need to output the parameters of a bivariate normal distribution.
To see what these parameters are, use the getParameterDescription method:
conditional.getParameterDescription()
Output:
[mean_0,standard_deviation_0,mean_1,standard_deviation_1,R_1_0]
which are respectively the mean of Y_1(x), the standard deviation of Y_1(x), the mean of Y_2(x), the standard deviation of Y_2(x), and the correlation coefficient of Y_1(x) and Y_2(x) (with value 0 if they are independent which is by default the case when you do Kriging with multiple outputs).