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I am trying to use chaospy for a 5d uncertainty analysis with point collocation method. My problem is that when I don't normalize the distribution to the reference values (don't divide by norm param), the standard deviations become very big, cp.Std(U_hat, dist), after fitting the polynomials with simulation results. cp.E(U_hat, dist) function works properly though. Maybe I don't quite understand the procedure, but shouldn't the method be independent of distribution normalizations?
Thanks! That was a very useful link! I think the tikhonov regularization was also causing the problem. Switched it to least square method, and it seems fine now!
Hi,
I am trying to use chaospy for a 5d uncertainty analysis with point collocation method. My problem is that when I don't normalize the distribution to the reference values (don't divide by norm param), the standard deviations become very big, cp.Std(U_hat, dist), after fitting the polynomials with simulation results. cp.E(U_hat, dist) function works properly though. Maybe I don't quite understand the procedure, but shouldn't the method be independent of distribution normalizations?
I have copied the code here:
-Payam
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