A simple y vs log(x) fit seems to work pretty well here:

fit <- lm(y ~ log(x))
summary(fit)

plot(y ~ log(x))
abline(fit)

On Fri, Dec 4, 2009 at 9:06 AM, Pascale Weber <pascale.weber@wsl.ch> wrote:

> Hi to all
>
> This is the first time I am quoting a question and I hope, my question is
> not too basic...
>
> For the following data, I wish to draw a fitted curve.
>
> x <- c(123,129,141,144,144,145,149,150,158,159,163,174,183,187,242,248)
>
> y <-
> c(14.42,26.96,31.3,19.95,36.36,15.4,24.76,35.39,28.07,40.97,26.23,42.83,46.53,14.79,49.18,48.08)
>
> If I plot the data, it looks somehow that a logistic function would render
> good results.
>
> My questions are:
>
> How do I use
>  nls and/or SSlogis (or other)
> to fit the curve?
>
> How can I see the summary statistics of the fit?
>
> How do I finally draw the line to my x,y (untransformed data) plot?
>
> Any help would be highly appreciated.
>
> Thank you and cheers
>
> Pascale
>
> --
> ____________________________________..___________________
>
> Dr. Pascale Weber
> Swiss Federal Research Institute WSL
> Zuercherstrasse 111
> CH-8903 Birmensdorf
> Switzerland
>
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>

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