Timeline for Fitting smooth monotonic function (low number of points, irregular grid)
Current License: CC BY-SA 4.0
5 events
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| Jul 31, 2023 at 21:10 | comment | added | JimB |
The fits certainly reproduce the data (especially with spec = 5 but that requires the estimation of 4, 2, 5, and 4 coefficients for the regressions, respectively. Despite the OP's claim that the observations are exact, 4 or 5 coefficients for just 8 data points is extreme at best. (Using spec = 10 for one of the regressions ends up with 9 coefficients!) As mentioned in my comment above, the OP's expectations are not realistic. But your answer with spec = 1 is good and the best that one can do.
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| Jul 31, 2023 at 17:46 | comment | added | Kvothe |
Thanks this now works much better with the higher SpecificityGoal. I would still hope to get an answer that uses the monotonicity of the data but this gives a quick decent fit.
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| Jul 31, 2023 at 16:57 | history | edited | Bob Hanlon | CC BY-SA 4.0 |
Added Manipulate to control SpecificityGoal
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| Jul 31, 2023 at 16:06 | comment | added | Kvothe |
Thanks for the suggestion. Unfortunately these fits are terrible. They are basically constant or linear and most don't even come close to even just a few points. This can be seen easily if you shift the different components to lie close together (add the line data=(# - {0, 0, 1, 1.2, 3.25}) & /@data for example to see this.
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| Jul 20, 2023 at 21:33 | history | answered | Bob Hanlon | CC BY-SA 4.0 |