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simultaneous nonlinear regression of a lot of data

• To: mathgroup at smc.vnet.net
• Subject: [mg65427] simultaneous nonlinear regression of a lot of data
• From: "dantimatter" <dantimatter at gmail.com>
• Date: Fri, 31 Mar 2006 06:09:24 -0500 (EST)
• Sender: owner-wri-mathgroup at wolfram.com

Hello all,

I have a question about using the nonlinear regression function on a
large data set.  Perhaps some of you have suggestions, and can point me
in another direction if this is not the best way to solve this problem.


Basically I have ~100 data sets of ~200 points each, and I'd like to
fit each set to the following function:

G(t) = 1/N * [ y / (1+t/m1) + (1-y) / (1+t/m2) ]

For each data set, the numbers N and y are different, but the numbers
m1 and m2 are the same for all data sets.  The problem is that I only
know m1, and not m2.  I am hoping to simultaneously solve all these
data sets to come up with a value for m2, but I'm not entirely sure how
to code it.  I can come up with a reasonable m2 to start any
regression. 

Any thoughts?

Thanks!