| T O P I C R E V I E W |
| karvek |
Posted - 05/22/2020 : 09:15:05 AM
Dear all,
I have a dataset that is peak-shaped, but rather than fitting a function using the nonlinear curve fitting, I perform an interpolation because I need perfect matching between the function and the points of the dataset.
Now, I have another dataset that is a superposition of the interpolated function (eventually scaled) plus another peak-shaped function.
I would like to use this knowledge on the originally interpolated function to find the other peak function that is hidden in the new dataset.
Is there any way I can perform a nonlinear curve fit to find the unknown peak-shaped function? Something like fitting a Gaussian + interpolated function?
Thanks for support. |
| 4 L A T E S T R E P L I E S (Newest First) |
| karvek |
Posted - 06/05/2020 : 09:34:13 AM
This last solution would be great to try.
Do you know how can I call "X" in OriginC to be any dataset/interpolated data and then run a nonlinear curve fitting?
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| lkb0221 |
Posted - 06/01/2020 : 09:47:05 AM
you can try setting up a custom fitting model (not sure if that would work or not). Something like:
Y = Scale * X + Gauss(X, y0, xc, w, A)
where X is your existing interpolated data; Scale, y0, xc, w & A are fitting parameters. |
| karvek |
Posted - 05/30/2020 : 05:18:39 AM
I know that the baseline have the same "shape" but I don't know how much is the integral, so I would like to have a scaling factor (a multiplier) as a free parameter of the fit. |
| snowli |
Posted - 05/22/2020 : 3:13:03 PM
How about using Analysis: Peaks and Baseline: Peak Analyzer?
Choose Fit Peaks as goal. On next page, specify Baseline Mode: Use Existing Dataset and specify the interpolated data as baseline.
Then the interpolated data will be removed from the data so you can fit to fit the peak of the data with baseline subtracted.
If I misunderstood, could you clarify?
Thanks, Snow |
