Here's the error:
Error -20116 occurred at Bad Regression.vi Possible reason(s): Analysis: Feasible solution not found.
Here's my code:
Here's my XY data:
7280 1.22858E+7 7312 1.25469E+7 7344 1.25722E+7 7376 1.21155E+7 7408 1.13621E+7
I noticed that if I scale down the Y, everything works out OK which tells me maybe I need to normalize my data some how. Is there some standard data prep and unprep for regressions like this?
Why are you using bisquare?
The constant term is 1 but x^2 is >10^14, making the problem ill conditioned. The matrix elements differ by >10^14 so there are not enough bits to sort it out.
Sorry, I take that back because you have x and y swapped (mislabeled!). Your x is 7280-7480, i.e. a small relative range. You get better results if you e.g. subtract the mean from x, for example. No scaling needed.
Sorry about the mislabel. Good catch! I guess I was asking more generally. I'm pretty sure for any given dataset, I can find some manipulation that helps it fit but is there a general way to preprocess your data before fitting?