Hello everyone. Using Python I have been able to do non-linear fits with lmfit creating a residual function for a potential mathematical function to fit, just as follows def pow_res(pars, E, data, sig): values = pars.valuesdict() a = values["a"] C = values["C"] model = C/E**a …

Does it always give the same answer? The fitting procedure is Levenberg Marquardt which is iterative and may only find a local minimum. Perhaps try a different starting point several times just to rule out this issue.

Actually, my initialization values give a curve more or less close to the one I should obtain with half-value weights. [image] However I tried changing the initialization values to half the ones I used and I obtained the same result again. [image]

Yes seems like the weights are not being taken into account. What version of LsqFit.jl are you using?

Thank you all. It was just as rafael.guerra said, the algorithm receives the weights as the inverse variances. Thank you all for your help! [image] l

The documentation says it’s minimizing sum(w_i*err_i) if you want it to take errors more seriously on the larger values you’d think that larger w would do it. So is there a problem with the documentation?

The Weighted Least Squares section of the documentation tutorial says: “We know the error variance and we set the weight as the inverse of the variance…”.

So is the tutorial at odds with the mathematical expressions in the docs? I’m on my phone it’s hard to figure out what’s what. Intuitively if it’s minimizing the sum of w*err and we make w bigger this means that error is more important. The OP tries to weight each error by 10% of the value of the m…

[image] dlakelan: So is the tutorial at odds with the mathematical expressions in the docs? No, it doesn’t look like that. From dimensional analyses, you can see that the weights wi in the following expression in the docs should have the same units as the inverse of a variance: [LsqFit] A…

Python lmfit takes weights into account, but Julia LsqFit package seems not to

General Usage

rafael.guerra November 23, 2022, 3:12pm 5

Just in case, the weights provided to LsqFit.jl should be inverse variances. See this other thread.

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Python lmfit takes weights into account, but Julia LsqFit package seems not to

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