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 Nonlinear fitting
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Karmar

United Kingdom
6 Posts

Posted - 04/27/2021 :  4:13:35 PM  Show Profile  Edit Topic  Reply with Quote  View user's IP address  Delete Topic
Hi,
I would like to create a new function for fitting the data. The function is y = exp(-(x/a)^b) with 0< = b <=1, but I have no idea what to put to Parameter Init.

Any help will be much appreciated.


Origin Ver. OriginPro 2021 (64-bit)
Operating System: WIN10

YimingChen

1592 Posts

Posted - 04/27/2021 :  4:19:48 PM  Show Profile  Edit Reply  Reply with Quote  View user's IP address  Delete Reply
Hi,

Please refer to this tutorial on defining a fitting function.
https://www.originlab.com/doc/Tutorials/UserDef-FitFunc

Step 7 shows settings of Initial Parameter. By default those values are set to 1. You can start with that for the fitting. If the fitting fails to converge, you may change the Initial guess to more random values. Again the initial guess depends on the data. If you still can't get good fit. Please send us your dataset.


James

Edited by - YimingChen on 04/27/2021 4:21:07 PM
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Karmar

United Kingdom
6 Posts

Posted - 04/27/2021 :  4:51:17 PM  Show Profile  Edit Reply  Reply with Quote  View user's IP address  Delete Reply
Thank you very much James. It has worked. I got the fit, but there is a huge error for a (80742,37162 ± 17881,27345). Is there anything else I can do to optimize the fit or my data are not good enough?
Data: 0, 1; 1800, 0.7; 3600, 0.61; 7200, 0.53; 14400, 0.5; 28800, 0.43; 57600, 0.39; 86400, 0.4
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YimingChen

1592 Posts

Posted - 04/28/2021 :  10:33:20 AM  Show Profile  Edit Reply  Reply with Quote  View user's IP address  Delete Reply
This is the optimal fitting result on this dataset. You may consider adding more data for less fitted error.

Yiming

quote:
Originally posted by Karmar

Thank you very much James. It has worked. I got the fit, but there is a huge error for a (80742,37162 ± 17881,27345). Is there anything else I can do to optimize the fit or my data are not good enough?
Data: 0, 1; 1800, 0.7; 3600, 0.61; 7200, 0.53; 14400, 0.5; 28800, 0.43; 57600, 0.39; 86400, 0.4


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