I'm fitting nonlinear functions to some growth data but I'm getting radically
different results in R to another program (Prism). Furthermore the values from
the other program give a better fit and seem more realistic. I think there is
a problem with the results from the r nls function. The differences only occur
with weighted data so I think I'm making a mistake in the weighting. I'm
following the procedure outlined on p 244 of MASS (or at least I'm trying to).
Thus, I'm using mean data with heteroscedasticity so I'm weighting by n/
variance, where the variance is well known from a large data set. This
weighting factor is available as the variable 'novervar'.
The function is a von Bertalanffy curve of the form
weight~(a*(1-exp(-b*(age-c))))^3. Thus I'm entering the command in the form:
solb1wvb<-nls(~sqrt(novervar)*(weight-(a*(1-exp(-b*(age-c))))^3),data=solb1.na.rm,start=list(a=0.85,b=0.45,c=0.48))
Can anyone suggest what I'm doing wrong? I seem to be folowing the
instructions in MASS. I tried following the similar instructions on page 450 of
the white book but these were a bit cryptic.
I'm using R 2.0.0 on a Windows 2000 machine
Regards,
Robert Brown
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