Hi Nelson, First of all, I doubt that changing from random to low-discrepancy sequence would affect this significantly. That will just mean that the the variation of the statistical parameters affecting the devices would be smoother for smaller numbers of samples, but I doubt it would make a massive difference to the distribution of your output measurements given that you have a reasonable number of samples already. I'd generally recommend LDS anyway over random, but the issue here is that what you're measuring appears to be discrete. It's still not clear what you're measuring. If it was the output of the inverter, then I'd expect that to be one of two values (1 or 0 - scaled by the voltage), but presumably you're measuring something else. When you say you're measuring the "hysteresis high of overtempt" it's not clear what you mean by that (I certainly don't know what you mean). What is the expression you're using? It can't just be the output voltage because the y values are too high. If the output is some kind of discrete measurement I wouldn't necessarily expect the circuit response to be gaussian. You don't really have "two peaks" you just have two values in the result measurements. The density estimator is meaningless in this case - you can see the y values (the red circles) are all lined up for two different values - so it's not two "peaks". If you looked at the Detail or Detail Transpose view it would be clear that all your measurements have one of two values. Regards, Andrew.
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