-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] On Behalf Of Martin Maechler
Sent: Tuesday, April 28, 2009 8:22 AM
To: Benedikt Niesterok
Cc: r-help at r-project.org
Subject: Re: [R] correlation coefficient
"BN" == Benedikt Niesterok <KleinerHaifisch at gmx.net>
on Tue, 28 Apr 2009 15:33:02 +0200 writes:
BN> Hello,
BN> I would like to get a correlation coefficient
(R-squared) for my model.
{{ arrrgh... how many people think they "need" an R^2 when they
fit a model ?? }}
BN> I don't know how to calculate it in R.
BN> What I've done so far:
BN> x<-8.5:32.5 #Vektor x
BN> y<-c(NA ,5.88 , 6.95 , 7.2 , 7.66 , 8.02 , 8.44 ,
9.06, 9.65, 10.22 ,
BN> 10.63 ,11.06, 11.37, 11.91 ,12.28, 12.69 ,13.07 ,
13.5 , 13.3 ,14.14 , NA , NA , NA , NA , NA) #Vektor y
BN> plot(y~x,col="green",pch=16,ylim=c(0,20),xlim=c(0,50))
BN>
(mod1<-nls(y~a+b*log(x,base=exp(1)),start=list(a=1,b=1),trace=TRUE))
This is a very *LINEAR* model.
Why don't you use lm()?
Then you'd even get your beloved R-squared ...
BN> xx<-seq(min(x),max(x),length=100)
BN> yy<-6.2456*log(xx)-7.7822
BN> lines(xx,yy,col="blue1")
BN> summary(mod1)
BN> This way I don't get R-squared like I do using the
command "lm" for linear
BN> models.
In general, R^2 is *NOT* easily defined for non-linear models.
R^2 is only defined if you have a nested sub-model, aka "null-model".
For linear models (*WITH* an intercept (!)), the sub-model is
naturally y ~ 1.
For general nonlinear models, the only simple sub-model is
'y ~ 0' which is often ridiculous to take as null-model, and
hence not taken by default.
More more on this, e.g. almost 7 years ago on R-help:
https://stat.ethz.ch/pipermail/r-help/2002-July/023461.html
Martin