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simultaneous fitting with one shared parameter

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I can try to do the similar algorithm of your vi, but I cannot see the block diagram of your program. Could you teach me how to do that?

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Message 11 of 16

Christian's example is excellent.  To help you get started I am attaching a simple example that may help.  The model is the sum of two exponential functions.  Each exponential has the form a*exp(b*x)+c, and the b parameter is shared across two data sets.  a and c are different for each of the two exponentials.



Message 12 of 16

I briefly looked at the example and it seems that this will be a great way to follow. I will work on and let you people know when I make more idea. 




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Message 13 of 16



I can understand your example except one thing. It seems to me that 2 other parameters are fixed, not really fitting parameters. Is it true? Or if they are fitting parameters, how can I get those returned values after fitting?

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Message 14 of 16
Accepted by topic author photoon

No, there are currently no other fitting paramters in Jim's example, partially because your original description is a bit confusing.


For example, you said "But, other three parameters are not supposed to be matched.", which could be understood that you don't want to fit for them at all. However, you meant that they should be different for each set (i.e. not shared), but still to be fit.


To rewrite for two unique paramters for each set and on shared parameter, you would rewrite it as follows, now with 5 parameters.

You should be easily able to adapt it to your problem.



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Message 15 of 16

Christian and Jim,


Now I completely understand your example. 

I really appreciate your solution.





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Message 16 of 16