I'll give you the equation of the reference I based my thinking upon. this the link: http://users.pandora.be/requested/images/equation.png
It's a sigmoid error function, but I thought I simplified things by picking a less complex form, although I think It won't matter that much. Anyway, as Ted suggested, this equation has the terms reparameterised into the form -(bx+c) as well. In my reference they probably tested for the b=0 scenario because they had an F-statistic. But to be honest I wouldn't know how to start implementing this? It seems a little more complicated then the ordinary stuff I normally do. Koen > -----Original Message----- > From: ecatchpole [mailto:[EMAIL PROTECTED] > Sent: donderdag 22 maart 2007 23:25 > To: Douglas Bates > Cc: Hufkens Koen; r-help@stat.math.ethz.ch; Philippe Grosjean > Subject: Re: [R] non-linear curve fitting > > Douglas Bates wrote on 03/23/2007 06:16 AM: > > On 3/22/07, Hufkens Koen <[EMAIL PROTECTED]> wrote: > > > >> Is there a means of getting an F-statistic (p-value) out > of all of this. > >> > > > > > >> Because least-square criterion / r-square only tell me how > good the fit is and not necessarily how solid this fit is. An > F-statistic (p-value) would be nice... > >> > > > > What would the F-statistic be? For a linear model with an > intercept > > the F-statistic represents a comparison of the model that > you have fit > > to the trivial model (intercept only). It is important that the > > models being compared are nested - otherwise the F statistic is of > > questionable validity. > > > > For the logistic growth model you described (which is not quite the > > one fit by SSlogis - that model has one more parameter, a > scale factor > > on the response) the response always goes to zero as x -> > -\Infty and > > to one as x -> \Infty. The trivial model is not nested within this > > model for finite parameter values so I'm not sure what hypotheses > > would be tested by an F-statistic. > > > > If the original curve is reparameterised as f(x) = > 1/(1+exp(-(a+b*x))), then you can test whether b=0. Is this any help? > > Ted. > > > >> Regards, > >> Koen > >> > >> > >> > >>> -----Original Message----- > >>> From: Philippe Grosjean [mailto:[EMAIL PROTECTED] > >>> Sent: donderdag 22 maart 2007 14:02 > >>> To: Hufkens Koen; r-help@stat.math.ethz.ch > >>> Subject: Re: [R] non-linear curve fitting > >>> > >>> Hello, > >>> > >>> If a least-square criterion is fine for you, you should > use nls(). > >>> For the logistic curve, you have a convenient self-starting model > >>> available: > >>> SSlogis(). Look at: > >>> > >>> ?nls > >>> ?SSlogis > >>> > >>> Best, > >>> > >>> Philippe Grosjean > >>> > >>> ..............................................<°}))><........ > >>> ) ) ) ) ) > >>> ( ( ( ( ( Prof. Philippe Grosjean > >>> ) ) ) ) ) > >>> ( ( ( ( ( Numerical Ecology of Aquatic Systems > >>> ) ) ) ) ) Mons-Hainaut University, Belgium > >>> ( ( ( ( ( > >>> .............................................................. > >>> > >>> Hufkens Koen wrote: > >>> > >>>> Hi list, > >>>> > >>>> I have a little curve fitting problem. > >>>> > >>>> I would like to fit a sigmoid curve to my data using the > >>>> > >>> following equation: > >>> > >>>> f(x) = 1/(1 + exp(-(x-c)*b)) (or any other form for that matter) > >>>> > >>>> Where x is the distance/location within the dataframe, c is > >>>> > >>> the shift of the curve across the dataframe and b is the > steepness > >>> of the curve. > >>> > >>>> I've been playing with glm() and glm.fit() but without any luck. > >>>> > >>>> for example the most simple example > >>>> > >>>> x = -10:10 > >>>> y = 1/(1 + exp(-x)) > >>>> glm(y ~ x, family=binomial(link="logit")) > >>>> > >>>> I get a warning: > >>>> non-integer #successes in a binomial glm! in: eval(expr, envir, > >>>> enclos) > >>>> > >>>> and some erratic results > >>>> > >>>> This is the most simple test to see if I could fit a curve > >>>> > >>> to this perfect data so since this didn't work out, > bringing in the > >>> extra parameters is a whole other ballgame so could > someone give me > >>> a clue? > >>> > >>>> Kind regards, > >>>> Koen > >>>> > >>>> > >>>> > > > > > -- > Dr E.A. Catchpole > Visiting Fellow > Univ of New South Wales at ADFA, Canberra, Australia > _ and University of Kent, Canterbury, England > 'v' - www.pems.adfa.edu.au/~ecatchpole > / \ - fax: +61 2 6268 8786 > m m - ph: +61 2 6268 8895 > > > > > > > > -- > No virus found in this incoming message. > Checked by AVG Free Edition. > Version: 7.5.446 / Virus Database: 268.18.16/729 - Release > Date: 21/03/2007 7:52 > > -- ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.