R help - Nov 2003 - problem plotting curve through data

I'm having trouble plotting a curve (basically a dose-response
function) through a set of data.

I have created a dataframe (df) of Stimulus Intensities (xstim) and
Normalized Responses (yresp), and I've used nls() to calculate a nonlinear
regression, like so:


--------------------
> f <- yresp ~ xstim^n / (xstim^n + B^n)
> starts <- list(n=.6,  B=11)
> myfit <- nls(formula=f, data=df, start = starts)
>myfit
Nonlinear regression model
  model:  yresp ~ xstim^n/(xstim^n + B^n)
   data:  df
        n         B
0.8476233 5.7943791
 residual sum-of-squares:  0.03913122
>
-----------

Which seems great, but I'd like to be able to plot this curve through my
data to see how the fit looks.

when I try:

------------
> plot(f,data=df)
Error in terms.formula(formula, data = data) :
	invalid power in formula
----------

or

----------
> n <- 0.87
> B <- 5.7
> plot(f,data=df)
Error in terms.formula(formula, data = data) :
	invalid power in formula
------------

If anyone can give me any tips on this "Error in terms.formula"
message,
or how functions are plotted over data, I'd be much obliged. I've only
been at about a R, some no explanations or suggestions are too simplistic.
Even an example of a plot of a logistic growth function of the form

R = S^n / ( S^n + S50^n)

where R is response, S is stimulus intensity and S50 is the intensity that
produces a 50% response

would be tremendously helpful



Cheers,

and many thanks,

Christian

-----------------------------------------------------------------------
Christian Reilly			http://www.stanford.edu/~heron
Hopkins Marine Station
Pacific Grove, CA 93950
heron at stanford.edu

Christian Reilly <heron at stanford.edu> writes:
> I'm having trouble plotting a curve (basically a dose-response
> function) through a set of data.
> 
> I have created a dataframe (df) of Stimulus Intensities (xstim) and
> Normalized Responses (yresp), and I've used nls() to calculate a
nonlinear
> regression, like so:
> 
> 
> --------------------
> > f <- yresp ~ xstim^n / (xstim^n + B^n)
> > starts <- list(n=.6,  B=11)
> > myfit <- nls(formula=f, data=df, start = starts)
> >myfit
> 
> Nonlinear regression model
>   model:  yresp ~ xstim^n/(xstim^n + B^n)
>    data:  df
>         n         B
> 0.8476233 5.7943791
>  residual sum-of-squares:  0.03913122
> >
> -----------
> 
> Which seems great, but I'd like to be able to plot this curve through
my
> data to see how the fit looks.
> 
> when I try:
> 
> ------------
> > plot(f,data=df)
> Error in terms.formula(formula, data = data) :
> 	invalid power in formula
> ----------
> 
> or
> 
> ----------
> > n <- 0.87
> > B <- 5.7
> > plot(f,data=df)
> Error in terms.formula(formula, data = data) :
> 	invalid power in formula
> ------------
Use predict.nls to get the fitted response curve.  See
?predict.nls
and especially the example, which you can run with
example(predict.nls)