[R] fitting with lm

[ggrothendieck@yifan.net]

This is just going to you since its not really about R.
If you are running Windows, check out
the CurveExpert software.  Use google to find
out where to download it from.   You can paste
your data into its spreadsheet and then one click
will run your data against numerous models, order
them by fit and display the data and the fit on a graph
for each one.  I have no connection with this package.

On 19 Mar 2002 at 21:19, Arne Mueller wrote:

> Thanks for pointing out nls, it seems to provide what I'm looking for. 
> Unfortunately, my daya distribution doesn't seem to be approxumated by 
> either a power-law nor by an exponential fucntion :-( but I may have to 
> play a little bit more with the params of the nls function.
> 
> 		regards,
> 
> 		Arne
> 
> Kaspar Pflugshaupt wrote:
> > On 19.3.2002 17:03 Uhr, Arne Mueller wrote:
> > 
> > 
> >>Dear All,
> >>
> >>I'm getting confused with the concept R uses to do regression using lm.
> >>I'm afmiliar with gnuplot and the build-in fit command, but couldn't get
> >>R's lm to work on my data.
> >>
> >>I know that my data follows a powerlaw or maybe an exponential function,
> >>and I'd like to determine the best fitting factors for the formula:
> >>a*x^b where b < 0.
> >>
> >>I've tried thge follwoing:
> >>
> >>s <- lm(y ~ x)
> >>
> > 
> > [...]
> > 
> > 
> >>What has R done? I assume the formula is just a+b*x and I can get a and
> >>b via
> >>
> >>
> >>>coef(s)
> >>>
> >>(Intercept)           x
> >>21.20917074 -0.06560878
> >>
> >>But:
> >>
> >>
> >>>s <- lm(y ~ a*x^b)
> >>>
> >>Error in terms.formula(formula, data = data) :
> >>      invalid power in formula
> >>
> >>I went through the formula section of the R-manual, but I realy don't
> >>get it.
> >>
> > 
> > Generally, you want to look at the nlm library to fit complicated functions
> > to your data. lm() does just linear models. In your case, however, you could
> > try a log-transformation to linearize (fitting log(y) ~ a + log(x) * b),
> > then re-transform the coefficients to the original scale.
> > 
> > 
> >>Finally, I'd like to have the raw data-points together with a line
> >>representing the function used to fit the data in a plot? How can I plot
> >>function, e.g. sin(x) ?
> >>
> > 
> > Look at help(curve). To add the results of any fit to an existing data
> > scatterplot, you can also use
> >  
> > lines(x.values, predict(your.model))
> > 
> > - if your x values are sorted by size. If not, use something like this:
> > x.order <- order(x.values)
> > lines(x.values[x.order], predict(your.model)[x.order])
> > 
> > 
> > 
> >>I hope I just need a primer on this to get going.
> >>
> > 
> > Hope that helps.
> > 
> > 
> > 
> > Kapsar Pflugshaupt
> > 
> > 
> > 
> 
> 
> 
> -- 
> Arne Mueller
> Biomolecular Modelling Laboratory
> Imperial Cancer Research Fund
> 44 Lincoln's Inn Fields
> London WC2A 3PX, U.K.
> phone : +44-(0)207 2693405      | fax :+44-(0)207-269-3534
> email : a.mueller at icrf.icnet.uk | http://www.bmm.icnet.uk
> 
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