Fitting an equation to a non-linear data set

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Alexander Richardson
Alexander Richardson am 2 Mär. 2019
Kommentiert: Star Strider am 3 Mär. 2019
I'm looking to try and fit an equation to this data set in the graph below (The x and y data are saved in two vetors both with n=401). I've tried using the Matlab curve fitting tool box but non of the options come close. Anyone got any idea's about the best way to proceed? I think the equation will take the form of an ODE? Thanks
angv.JPG

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Star Strider
Star Strider am 2 Mär. 2019
Fit your data by modeling the process that created them, and estimating the parameters of that model.
We can probably help if we have that information, and a description of the process and the model.
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Alexander Richardson
Alexander Richardson am 3 Mär. 2019
Thank you for your help!
Star Strider
Star Strider am 3 Mär. 2019
As always, my pleasure!

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John D'Errico
John D'Errico am 3 Mär. 2019
Bearbeitet: John D'Errico am 3 Mär. 2019
This is an example of a case where you have no reason to use any specific nonlinear model. Your hope that an ODE might be appropriate seems to have no real basis in where the data came from. Yes, in theory, all models of physical systems can arguably be described as an ODE. But without the ODE, there is little reason to go down that avenue, as the use of an ODE itself causes some additional complexities.
But where does that leave you? I would suggest that since the data itself does not appear to be seriously contaminated with random noise, yet you have no real candidate for a model, this makes your problem well suited to fit with an interpolating spline. And while the many parameters that define a spline will be of absolutely no value to you in terms of understanding the process, what meaning would you assign to the parameters of some other random function that just happens to predict the behaviour of that same curve? That is, if you were to choose some model just because it happens to be able to approximate your data sufficiently well, the parameters of that function are also relatively useless, since the model was chosen for no reason other than that it approximates one specific curve.
So just use a spline model. (In fact, one can even show that a spline is the solution of a specific differential equation model. But introducing that ODE into the problem does not offer any real value.) The specific spline you use may depend on issues that have not been discussed. For example, if there is some need for smoothing, then a smoothing or least squares psline might be pertinent. If a classical spline is a problem due to ringing/oscillations, then a pchip interpolant might be appropriate. What are the appropriate boundary conditions on the spline? (Again, the roots of a spline in an ODE come into play, but only peripherally.)
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John D'Errico
John D'Errico am 3 Mär. 2019
Yes, but my point is there has been no model identified or posed. You cannot estimate parameters in an unspecified model.
Star Strider
Star Strider am 3 Mär. 2019
My impression, as the conversation unfolded, is that finding a model is the purpose of the post.

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