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    $\begingroup$ You might want to use NonlinearModelFit[] instead, so that getting the required data is convenient: nlm = NonlinearModelFit[data, model, parameters, x]; Export["filename.dat", Transpose[{data[[All, 1]], data[[All, 2]], nlm["PredictedResponse"], nlm["FitResiduals"]}], "Table"]. $\endgroup$ Commented Mar 20, 2018 at 13:42
  • $\begingroup$ I tried your suggestion with nlm, but unfortunately mma was not possible to solve the model as with FindFit, even though according to the documentation it should solve in the same way. Is it possible to "catch" the calculated values of Findfit in a table and export them? $\endgroup$ Commented Mar 21, 2018 at 8:52
  • $\begingroup$ NonlinearModelFit[] uses FindFit[] internally, so it doesn't make sense that one works and the other does not. Did you remember to include constraints and starting values? Also, since you included neither your raw data nor your model in your question, I have no way of knowing whether you used it right. $\endgroup$ Commented Mar 21, 2018 at 8:59
  • $\begingroup$ Of course it doesn't make sense. Maybe you have more insight to my problem right now by adding model, parameter and data. I tried the same constraints and starting values in nlm. $\endgroup$ Commented Mar 21, 2018 at 9:24
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    $\begingroup$ My data are about absorption (-) over frequency (1/s). That means, first value 00143.7500 = frequency = 143.75 1/s and second value is corresponding absorption 0000.0793 = absorption = 0.0793; next freqeuncy value is 487.5 and corresponding absorption is 0.2002. The format with all the 0 is due to Excel export. $\endgroup$ Commented Mar 21, 2018 at 15:14