[proFit-list] statistically valid fit?

[pro Fit Support]

>I have data from kinetics experiments that I'd like to fit.  The 
>differential equations describing the mechanism can be integrated, 
>but the resulting equation is unusual; it cannot be expressed as 
>concentration as a function of time.  However, it can be manipulated 
>to give   t = F(concentration).  It would be easy to fit data in pro 
>Fit to this equation.  But...
>
>But this is wrong statistically, isn't it?  In my case, t is the 
>(experimental) independent variable, and the error on it is very 
>small compared to the error on the (experimental) dependent variable 
>- the concentration.  Isn't it improper to use standard fitting 
>algorithms in such a case, i.e., isn't it implicitly assumed that the 
>error on the independent variable is negligible?  Unfortunately, I 
>can't transform my function so that concentration = f(t).
>
>Any thoughts on how to obtain valid fits with valid errors on the 
>parameters?
>
>ciao,
>Bruce

Note that you can specify errors for both independent and dependent variable in pro Fit (please see the chapter on fitting in the handbook). Alternatively, you can use the Roots predefined call to calculate the inverse of your function and fit that. It may take longer, but speed may be irrelevant on today's machines.
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