Various parameter/stats fixes#112
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Otherwise `yfun(b)` will be returned instead of `b`, which is confusing (e.g. `log(b)` instead of `b` for exp/power fits)
Fitting King curves is done by linearizing the model, but recovering the parameters can't be handled by `LinearCurveFitAlgorithm` applying the inverse y-transform alone because the `A` and `B` parameters of the King model are related to each other. Previously this also gave inaccurate initial guesses for `ModifiedKingCurveFitAlgorithm`. The Jacobian was also incorrect since it was computed using the linear Jacobian formula. Now there's a `KingCurveFitAlgorithm` type to dispatch on and recover the parameters, and the correct analytical Jacobian is used.
The old branch would have optionally taken the residuals from the liinearized model, which would not be correct.
The residuals of a linear fit are stored in original y-space, so if a transform was applied to y we would end up computing the Jacobian for a linear model on them.
This was referenced Jun 26, 2026
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This has a bunch of fixes that I found when looking into #110:
exp(b+a*x)instead ofb*exp(a*x)#110.LinearCurveFitAlgorithmanyway. The Jacobian was wrong too. Now it has its own algorithm type. This wasn't caught by the tests before because we weren't checking the fitted parameters against the real parameters.5d6afa4 and fe8210a are technically breaking, but I would consider them a bug fix since I don't think anyone would expect the old behaviour, so I bumped the version to 1.9.3.
Written with a lot of help from Claude 🤖 Alternative to #111.
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