Surface fitting to data
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Folks,
I have a custom equation with z=a*x*y which I want to fit to some experimental data. The challenge is that
1) The fit z needs to be calculated for 8 different items. For simplicity, we use the same x,y for each item. Then the sum of these 8 items will compared against the experimental data to which I want to fit.
2) Is this possible either through a) SFTOOL and/or B) Programmable approach?
Thanks in advance B
4 Comments
Sean de Wolski
on 11 Oct 2013
It needs to be calculated 8 times for the same x and y on each but a different, z?
Answers (2)
Sean de Wolski
on 11 Oct 2013
Edited: Sean de Wolski
on 11 Oct 2013
The curve/surface fitting tool will work for you application. Design the fit within the application, then go to
File -> Generate Code
This will generate a function that you can then save and call with your new z-data. Each time it will return a fit object based on the new z.
Alternatively, you could use LinearModel.fit in the Statistics Toolbox
doc LinearModel.fit
or lsqcurvefit in the Optimization Toolbox, though this is overkill:
0 Comments
Matt J
on 11 Oct 2013
Edited: Matt J
on 11 Oct 2013
And "a" is the parameter to be fit? sftool seems like overkill for something that can be done as simply as
a=x(:).*y(:)\z(:);
5 Comments
Matt J
on 11 Oct 2013
The solutions x,y for the equation
z=a*x*y
are not unique. You have 1 equation in 2 unknowns. So your problem appears under-specified.
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