April Lindeman <aprillindeman <at> yahoo.com> writes:
> I am trying to compare Vbert growth curves from several years of > fish data. I am following the code provided by: > http://www.ncfaculty.net/dogle/fishR/gnrlex/VonBertalanffy/VonBertalanffy.pdf. > Specifically the section on VBGM Comparisons between groups. > This code is pretty cut and dry. I am able to run it perfectly with > the "fake" data that is provided. But when I run it with my own data > I get stuck with this line: fitGen <- > nls(vbGen,data=LMB,start=svGen) > I get this error code: Error in numericDeriv(form[[3L]], names(ind), env) : Missing value or an infinity > produced when evaluating the model. > Does anyone know how to fix it? I have no missing values and do not know how to fix the infinity produced. > Here is my data set: structure(list(Age = c(1L, 2L, 3L, 5L, 1L, 2L, > 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, > 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), MM = > c(155.79, 296.37, 325.77, 374.65, 181.46, 258.31, 321.88, 355.6, > 139.75, 230.72, 319.61, 344.84, 130.92, 236.34, 290.53, 360.33, > 400.61, 155.33, 240.87, 315.46, 345.05, 378.2, 134.71, 256.66, > 333.71, 362.99, 381.46, 153.91, 217.21, 287.8, 357.28, 385.62, > 222.25, 288.93, 294.05, 332.79, 367.39), Year = c(2005L, 2005L, > 2005L, 2005L, 2006L, 2006L, 2006L, 2006L, 2007L, 2007L, 2007L, > 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, > 2009L, 2009L, 2010L, 2010L, 2010L, 2010L, 2010L, 2011L, 2011L, > 2011L, 2011L, 2011L, 2012L, 2012L, 2012L, 2012L, 2012L)), .Names = > c("Age", "MM", "Year"), class = "data.frame", row.names = c(NA, > -37L)) > In case it's helpful here is all my code before this point: > str(LMB) > MMi=as.integer(MM) > Yearf=as.factor(Year) > Agei=as.integer(Age) > ( svCom <- vbStarts(MMi~Agei,data=LMB)) > ( svGen <- lapply(svCom,rep,2) ) > vbGen <- MMi~Linf[Yearf]*(1-exp(-K[Yearf]*(Age-t0[Yearf]))+error) > fitGen <- nls(vbGen,data=LMB,start=svGen) I believe that the reason you're running into trouble is that you have a very small number of data points per year. You're trying to fit a three-parameter model to at *most* 5 data points per year, and at least 4 (2005-2007 have only 4 ages, 2008-2012 have 5 ages). In principle this should be possible, but nls is a little bit fragile and so it gets in trouble. I wasn't able to run all your code because some of the packages you use seem to be unavailable for the development version of R I'm using ... The following solution works for me. You may be better off fitting a nonlinear mixed model, but I don't have time to work out that example at the moment ... LMB <- structure(list(Age = c(1L, 2L, 3L, 5L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), MM = c(155.79, 296.37, 325.77, 374.65, 181.46, 258.31, 321.88, 355.6, 139.75, 230.72, 319.61, 344.84, 130.92, 236.34, 290.53, 360.33, 400.61, 155.33, 240.87, 315.46, 345.05, 378.2, 134.71, 256.66, 333.71, 362.99, 381.46, 153.91, 217.21, 287.8, 357.28, 385.62, 222.25, 288.93, 294.05, 332.79, 367.39), Year = c(2005L, 2005L, 2005L, 2005L, 2006L, 2006L, 2006L, 2006L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2010L, 2010L, 2010L, 2010L, 2010L, 2011L, 2011L, 2011L, 2011L, 2011L, 2012L, 2012L, 2012L, 2012L, 2012L)), .Names = c("Age", "MM", "Year"), class = "data.frame", row.names = c(NA, -37L)) library(ggplot2) LMB$Yearf <- factor(LMB$Year) (g0 <- ggplot(LMB,aes(Age,MM))+geom_point(aes(colour=factor(Year)))) (g2 <- g0 + geom_smooth(aes(colour=factor(Year)),se=FALSE,method="auto",span=2)) n1 <- nls(MM~SSasympOff(Age,Asym,lrc,c0),data=LMB) pframe <- data.frame(Age=seq(1,5,length.out=50)) pframe$MM <- predict(n1,newdata=pframe) (g1 <- g0+geom_line(data=pframe)) library(nlme) nyear <- length(unique(LMB$Year)) svec <- c(rbind(coef(n1), matrix(0,nrow=nyear-1,ncol=length(coef(n1))))) fit2 <- gnls(MM~SSasympOff(Age,Asym,lrc,c0),data=LMB, params=Asym+lrc+c0~Yearf, start=svec) printCoefmat(summary(fit2)$tTable) pframe2 <- expand.grid(Age=seq(1,5,length.out=50), Year=unique(LMB$Year)) pframe2$Yearf <- factor(pframe2$Year) pframe2$MM <- predict(fit2,newdata=pframe2) g0 + geom_line(data=pframe2, aes(colour=factor(Year))) ______________________________________________ R-help@r-project.org 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.
