Subject: Sum: nonlinear regressions

From: Roy Jensen <[email-masked]>
Date: Fri, 28 Apr 2000 12:32:25 -0700

If the problem relates to the magnitude, can you normalize your values
and then fit the data. Changing the convergence criteria [from their
lose defaults] is a must.

We are using Excel Solver to determine optimum parameters for an
experiment under development by inputting the equations of motion --
it takes a while but converges 

A third year undergraduate lab uses Excel Solver to fit the
rovibrational IR spectrum of HCl and DCl to determine the
spectroscopic constants. If the function is input correctly, Solver
converges to the correct solution [almost] independent of the initial
parameters.

I would be willing to play with one of your data files if you are able
to send it to me: [email-masked]

Roy Jensen

>>4.  Roy Jensen
>>Excel and Quattro Pro can fit to non-linear functions. They are not free but 
>>you probably have one on your computer. I have found the Excel Solver to be
>>very stable.
>
>I use Excel's Solver to fit power curves (y=ax^b) to experimental data by
>minimising SSE and find it sometimes produces far from optimal solutions,
>even though it believes convergence was achieved. Tweaking the parameters
>from their defaults helps but I still haven't got it 100% reliable. The
>problem is related to the magnitude of the data, i.e. data sets with x
>values above a certain value consistently don't work. I'd recommend thorough
>testing of any fitting routine you develop using Solver!
>
>Alternatively, if anyone has a good suggestion as to what I might be doing
>wrong, I'd be very interested to hear it...
>