# [R] An error in fitting a non linear regression

Petr PIKAL petr.pikal at precheza.cz
Tue Feb 24 11:48:06 CET 2009

```Hi

r-help-bounces at r-project.org napsal dne 24.02.2009 11:31:22:

>
> Hi,
>
> Thank you for the reply and suggestions.
>
> I have two questions?
> 1) If I want to use log, it seems that I have to take log from both
sides of
> the model which will lead to lm(log(q)~log(-depth)). What is
tehdifference
> between this syntax and lm(log(q) ~ I(-depth))?

If you have

y = a*exp(-b*x) then log of this equation is

log(y) = log(a) - b * x

at least I was told that by my teacher back at school some decades ago
that log(exp(x)) = x.

You can prove it by

log(exp(whatever))

interactively in R

Regards
Petr

>
> 2) How can I calculate the R-squared of a fitted non linear model?
>
> Regards
> Saeed
>
>
> Christian Ritz-3 wrote:
> >
> > Hi Saeed,
> >
> > one approach is to try out several initial value combinations for a
and b.
> >
> > It often helps to find initial values of the same order of magnitude
and
> > of the same sign
> > as the final estimates.
> >
> > To get such initial values, you could linearize the model:
> >
> > lm(log(q) ~ I(-depth))
> >
> >
> > and supply the estimated coefficients from the linear regression as
> > starting values:
> >
> > nreg <- nls(q ~ a*exp(-b*depth), start = list(a = 0.76168, b =
-0.08484))
> > summary(nreg)
> >
> >
> > Christian
> >
> > ______________________________________________
> > R-help at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
>
> --
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http://www.nabble.com/An-error-in-fitting-a-non-
> linear-regression-tp22118160p22179525.html
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>
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