I am using the PCE model to model the input-output relationship. Specifically, my input is defined using kernel estimator and Gaussian copula:
iOpts.Marginals = uq_KernelMarginals(solar_power’);
C = corr(solar_power’,‘Type’, ‘Spearman’);
iOpts.Copula.Type = ‘Gaussian’;
iOpts.Copula.RankCorr = C;
where solar_power is my data matrix, with 30 dimension and 17520 observations.
Then I force the PCE model to use the Hermite basis by commanding (I think this procedure will automatically uses the Nataf transformation):
where p is a 1*30 cell containing ‘Hermite’.
After building the PCE model. I try to evaluate the outputs using my original 17520 observations:
YPC = uq_evalModel(solar_power’);
I found that for most observations, it returns normal values. However, for some observations, e.g., for the 1306th observation, the values of the multiple outputs contain NaN, Inf, -Inf, or normal values.
I am very confused about this. If I have built a PCE model, how can I get NaN or Inf value for a given observation?