Re: Curve Fitting to Exponential Data

Thank you very much for your reply.

You say there is a non-zero "horizontal"
asymptote, and you haven't placed it in your model

Try y=A*e^(Bx)+ C

Even better, you might want to MEASURE your asymptotic value, subtract it a
priori from your data, and then estimate your original model.

I've tried this and it resulted in this superior looking graph:
http://i81.photobucket.com/albums/j201/tacoflies/sample_and_curve2.png

There was a significant issue though:
The curve fitting method I linked to above involves taking ln(y). When
y is below the asymptote and I subtract the asymptote value, y is
negative and ln(y) is undefined.
To avoid this problem I ignored any values of Y where y <= 0, but this
obviously will alter my resulting fitted curve. Actually, thinking
about it some more, this only happens with the least reliable data, so
maybe it's not a big deal.

Since datapoints at lower X's are more reliable than those at higher
X's perhaps I should be doing some weighting in my curve fitting
calculations?

Off the cuff, this looks a little double exponentially to me, or

y=Ae^(Bx) + Ce^(Dx) + F

Looking at the curve fit now, do you still think think that
distribution looks double exponential...? I think I can forget about
solving it if it is!

.

Relevant Pages

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