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MikeR43
 Post subject: Curve fitting with noisy sensor data — best approach?
PostPosted: Mon Mar 30, 2026 10:29 pm 
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Joined: Mon Mar 30, 2026 10:26 pm
Posts: 1
Hi all, I just discovered ALGLIB and I'm impressed by the range of numerical tools available.

I'm working on a project where I need to fit a polynomial curve to sensor data that has quite a bit of noise. I've been using basic least squares in Python but the results aren't great when the noise spikes.

Has anyone here used ALGLIB's fitting functions for something similar? I'm particularly interested in whether the spline fitting or the LSFit routines handle outliers well, or if I should be pre-filtering the data first.

Any tips from people who've dealt with real-world noisy data would be appreciated. Thanks!

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