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Using FindPeak on some datapoints, I have found the positions and values of likely Gaussian peaks which form the data. The format is {x, y} and the list generated by FindPeak is here. Now I wish to incorporate these values into a FindFit function somehow. I have seen it used like this before: FindFit[MassSpecData, Model, IndependentVariable, Parameters] /. FindPeaks[MassSpecData, Gaussian], but this is somewhat vague. The model should be a sum of Gaussians, each corresponding to the peak values found.

This is my attempt

dataconfig = {A[#], μ[#], σ[#]} & /@
   Range[Length@gausspeaksofdata3];
zerod = {A[#], 0, σ[#]} & /@ Range[Length@gausspeaksofdata3];
gaussian[A_, μ_, σ_, x_] =
  A^2 E^(-((x - μ)^2/(2 σ^2)));

FindFit[adjusteddata, {gaussian[##, x] & @@@ dataconfig // Total,
  gaussian[##] & @@@ zerod = Flatten@gausspeaksofdata3[[All, 2]], x} ,
  Flatten@dataconfig, x]
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  • $\begingroup$ try putting code when possible in post. i almost missed it under a huge data list. $\endgroup$ Oct 30, 2015 at 13:30
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    $\begingroup$ Your data has hundreds of peaks. Why not try a simpler problem with only a few peaks, get things working in that case, and then generalize? $\endgroup$
    – bill s
    Oct 30, 2015 at 13:31
  • $\begingroup$ I gave an answer to your privious similar question that make the whole tihng simpler. $\endgroup$ Oct 30, 2015 at 13:33

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