In order to find the FWHM I need to find a Gaussian f corresponding to a set of (x,f(x)) values. The available fitting methods (I'm restricted to C#) assume the solution to be a polynomium of n'th degree (or that's what I've been able to find so far). I'm wondering if there exists a specialized fitting method/scheme aimed at finding Gaussians. Or is there a generalized method out there that converges fast? I can provide a good guess for the middle of the bell curve and its height but no more than that.
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See the fowlloing post: http://stackoverflow.com/questions/10950733/gaussian-curve-fitting-algorithm. It simply estimates the average and standard deviation to obtain the gaussian fit. – Alex Jan 26 '17 at 13:31
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Thanks for your link. This is for finding the Gaussian g for a function f, so that g describes the properties of f. I have sample points for the Gaussian, not the dataset. – beyond Jan 26 '17 at 13:53
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Solved this by observing that
ln(y) = ln(a) - ½(x-b)^2/c^2
which gives
c = sqrt(½(x-b)^2/ln(a-y))
So with a and b known it was a no-brainer :)

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