Hello,
Using this data:
http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt
and the following code i got the image at the end of this message:
US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep="
")
US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE)
f.US1<-function(x){coef(US.nls.1)["a"]*x^coef(US.nls.1)["b"]+coef(US.nls.1)["c"]}
xvals.US1<-seq(min(US.final.values$WTD),max(US.final.values$WTD),length.out=75)
yvals.US1<-f.US1(xvals.US1)
Rsq.nls.1<-sum((predict(US.nls.1)-mean(US.final.values$ECe))^2/sum((US.final.values$ECe-mean(US.final.values$ECe))^2))
plot(US.final.values$WTD,US.final.values$ECe,col="red",pch=19,cex=.75)
lines(xvals.US1,yvals.US1,col="blue")
but the r^2 wasn't so hot.
Rsq.nls.1
[1] 0.2377306
So I wanted to try a different equation of the general form a/(b+c*x^d)
US.nls.2<-nls(US.final.values$ECe~(a/(b+c*US.final.values$WTD^d)),data=US.final.values,start=list(a=100.81,b=73.7299,c=0.0565,d=-6.043),trace=TRUE,algorithm="port")
but that ended with "Convergence failure: false convergence (8)". I
tried
relaxing the convergence criteria to no avail. Assuming the form of the
equation I'm trying to use is the problem, I've been unable to track
down a
source that shows the shapes of various non-linear equations that I might be
able to try as alternatives. Any suggestions?
http://n4.nabble.com/file/n1676330/nls_image.jpg
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emorway wrote:> > > So I wanted to try a different equation of the general form a/(b+c*x^d) > > US.nls.2<-nls(US.final.values$ECe~(a/(b+c*US.final.values$WTD^d)),data=US.final.values,start=list(a=100.81,b=73.7299,c=0.0565,d=-6.043),trace=TRUE,algorithm="port") > > but that ended with "Convergence failure: false convergence (8)". I tried > relaxing the convergence > >You want 4 parameters from a set of data that has a very large variance. Try to fix d and c to a reasonable constant; it probably will converge.>From looking at your data and the variances, I would suggest tolog-transform first. If you feel bad about it, you can always fit the original data later after you have found a good model. Dieter -- View this message in context: http://n4.nabble.com/different-forms-of-nls-recommendations-tp1676330p1676547.html Sent from the R help mailing list archive at Nabble.com.
On Sat, 2010-03-20 at 14:55 -0800, emorway wrote:> Hello, > > Using this data: > http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt > > and the following code i got the image at the end of this message: > > US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep=" ") > US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE) > f.US1<-function(x){coef(US.nls.1)["a"]*x^coef(US.nls.1)["b"]+coef(US.nls.1)["c"]} > xvals.US1<-seq(min(US.final.values$WTD),max(US.final.values$WTD),length.out=75) > yvals.US1<-f.US1(xvals.US1) > Rsq.nls.1<-sum((predict(US.nls.1)-mean(US.final.values$ECe))^2/sum((US.final.values$ECe-mean(US.final.values$ECe))^2)) > plot(US.final.values$WTD,US.final.values$ECe,col="red",pch=19,cex=.75) > lines(xvals.US1,yvals.US1,col="blue") > > but the r^2 wasn't so hot. > Rsq.nls.1 > [1] 0.2377306 > > So I wanted to try a different equation of the general form a/(b+c*x^d) > > US.nls.2<-nls(US.final.values$ECe~(a/(b+c*US.final.values$WTD^d)),data=US.final.values,start=list(a=100.81,b=73.7299,c=0.0565,d=-6.043),trace=TRUE,algorithm="port") > > but that ended with "Convergence failure: false convergence (8)". I triedHi emorway, Do you have 657 obs and 4 parameters to fit. In my opinion you have few obs... I think do you fit in steps: US.nls.2<-nls(ECe~(a/(b + c * WTD^d)),data=US.final.values,start=list(a=100.81,b=73.7299,c=0.0565,d=-6.043),trace=TRUE,algorithm="port") temp_nls1 <- nls(ECe~(100/(73 + .05 * WTD^d)),data=US.final.values,start=list(d=-6.043),trace=TRUE,algorithm="port") temp_nls2 <- nls(ECe~(100/(73 + .05 * WTD^d)),data=US.final.values,start=list(d=-1.01613),trace=TRUE,algorithm="port") temp_nls3 <- nls(ECe~(100/(73 + c * WTD^(-1.01613))),data=US.final.values,start=list(c=0.05),trace=TRUE,algorithm="port") temp_nls4 <- nls(ECe~(100/(73 + c * WTD^(-1.01613))),data=US.final.values,start=list(c=-14.7127),trace=TRUE,algorithm="port") temp_nls5 <- nls(ECe~(100/(b-14.7127 * WTD^(-1.01613))),data=US.final.values,start=list(b=73),trace=TRUE,algorithm="port") temp_nls6 <- nls(ECe~(100/(b-14.7127 * WTD^(-1.01613))),data=US.final.values,start=list(b=70.4936),trace=TRUE,algorithm="port") temp_nls7 <- nls(ECe~(a/(70.4936-14.7127 * WTD^(-1.01613))),data=US.final.values,start=list(a=100),trace=TRUE,algorithm="port") 0: 2243.9898: 100.000 1: 2122.8218: 106.219 2: 1359.8819: 187.530 3: 1359.8819: 187.530 -- Bernardo Rangel Tura, M.D,MPH,Ph.D National Institute of Cardiology Brazil