Using assumptions while curve fitting
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Hello all,
I have a simple (I think!) question. I have an xy data set that I need to fit to a custom equation. x values range from 0 to 500 (they are concentrations, so negative values are unphysical/nonsensical), y values range from ~135 to 260.
The issue is this. The custom equation I need is a hyperbola. For x>0 the hyperbola the curve fitting tool solves for is excellent. However, I am left (in the curve fitting window) with a chunk of the hyperbola that is also for x<0. This piece of the function, which is nowhere near a data point, seems to be leading to an artificially low R^2 and other goodness-of-fit statistics.
Can I build an assumption into the curve fitting tool or command line fitting procedure where my custom equation assumes x>=0 and so yields reasonable goodness-of-fit values?
Thank you sincerely for any assistance you can provide!
Sam
1 个评论
Walter Roberson
2013-8-29
Which routine are you using to do the fitting?
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Shashank Prasanna
2013-8-29
0 个投票
Curve fitting tools will fit the equation you are trying to model. This equation may very well only be called for values of x < 0.
Since R^2 is computed purely by using your data - which I assume does not have x < 0 values, then what you see there is a purely visual artifact. You can continue to use the fitted model for your x > 0 only.
If this does not help, could you provide details on what is the exact equation you are trying to fit as well as how the data looks.
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