5 ms·
What you are describing is a very real danger, but if you are modeling actual noise, it's less of a risk than if you are modeling some small systematic shift th
by lutorm 16y ago
What you are describing is a very real danger, but if you are modeling actual noise, it's less of a risk than if you are modeling some small systematic shift that you claim you must subtract from the signal. With noise, it's more unlikely that the model would just by chance give a systematic shift to the data. More likely, if the model is wrong, it just won't decrease the noise level.
- ars 16y agoIt's was actually systematic shift, but a periodic one. It wasn't random noise.
- lutorm 16y agoWell, true. If the noise was truly random, you couldn't model it, of course. I just meant "noise" in the sense of "apparently random variations that actually aren't random".
- starwed 16y agoThat's not quite true, since a small signal+random noise will certainly give you a prediction that is testable.