Wrong second-order effects for lognormal inputs

[gnopik]

Python package (and dashboard) returns wildly negative second-order effects for independent inputs, if one of them is lognormal and another uniform (I haven't tested other combinations). In the Matlab package, the second-order is adequate.

Source: The difference is that in MATLAB we have a custom binning function, while in Python we use a ready-made one from some library.

Solution: So I guess there is no better solution than adopt the Matlab binning algorithm to Python as well.

Example.

(Matlab for the same problem with lognormal interest_rate returns a meaningful SOE=0.01)

[tupui]

Are we seeing the same thing on the scatter plots? Because the bottom one does not show a lognormal distribution.