fitting - Test Goodness of fit for FindFit

Is there any way to get an estimate of the goodness of fit from FindFit, for instance getting the final error? The documentation doesn't provide any hints, and a quick Google search didn't return any useful link either. Am I missing something obvious?

Answer

You can use NonlinearModelFit instead of FindFit.

dt = Table[Prime[x], {x, 20}];

FindFit[dt, a x Log[b + c x], {a, b, c}, x]
(* {a -> 1.42076, b -> 1.65558, c -> 0.534645} *)

nlm = NonlinearModelFit[dt, a x Log[b + c x], {a, b, c}, x];
Normal[nlm]
(* 1.42076 x Log[1.65558+0.534645 x]*)

nlm["ParameterTable"]

enter image description here

Grid[Transpose[{#, nlm[#]} &[{"AdjustedRSquared", "AIC", "BIC", "RSquared"}]], Alignment -> Left]

enter image description here

See: NonlinearModelFit >> Properties >> Goodness of fit measures

Comments

plotting - Filling between two spheres in SphericalPlot3D

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plotting - Plot 4D data with color as 4th dimension

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plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1.

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