[R] Error in library (nls)

[matotope]

Hi Ben,
thanks for your advise. I put the comment in front of the line with nls. Now
the message doesn't appear but the script won't produce the result files
which I need (the result files are empty). 
When executing the script, R asks for number of iterations and after that it
states "Read 20 items" but nothing happens. Probably also some other part of
the script needs to be amended.

Here is the script:

#library (nls)
options (digits = 6, show.error.messages=FALSE)

cat ("Enter the number of iterations: ")
niter<-as.integer (readLines(n = 1))
cat ("Parameter a (asymptote) for Kohn's equation", file="Param_a_Kohn.txt",
append=TRUE, fill=TRUE)
cat ("Number of iterations: ",niter, file="Param_a_Kohn.txt", append=TRUE,
fill=TRUE)
cat ("     Niter      Min     Mean     Max     Sd",
file="Param_a_Kohn.txt",append=TRUE, fill=TRUE)
cat ("Parameter b for Kohn's equation", file="Param_b_Kohn.txt",
append=TRUE, fill=TRUE)
cat ("Number of iterations: ",niter, file="Param_b_Kohn.txt", append=TRUE,
fill=TRUE)
cat ("     Niter      Min     Mean     Max     Sd",
file="Param_b_Kohn.txt",append=TRUE, fill=TRUE)
cat ("Parameter a (asymptote) for Eggert's equation",
file="Param_a_Eggert.txt", append=TRUE, fill=TRUE)
cat ("Number of iterations: ",niter, file="Param_a_Eggert.txt", append=TRUE,
fill=TRUE)
cat ("     Niter      Min     Mean     Max     Sd",
file="Param_a_Eggert.txt",append=TRUE, fill=TRUE)
cat ("Parameter b for Eggert's equation", file="Param_b_Eggert.txt",
append=TRUE, fill=TRUE)
cat ("Number of iterations: ",niter, file="Param_b_Eggert.txt", append=TRUE,
fill=TRUE)
cat ("     Niter      Min     Mean     Max     Sd",
file="Param_b_Eggert.txt",append=TRUE, fill=TRUE)

#construction of the dataset to estimate the parameter from output file from
GEMINI
createdata<-function(n, niter=500) {
concent<<-function(echa) apply(matrix(1
:length(echa),ncol=1),1,flocal1,pop=echa)
flocal1<-function(pop,j) length(unique(pop[1:j]))
indsel<-length (n)
if (indsel<=1) stop ("n>1 expected")
faesel<-sum(n)
echa<-rep(1:indsel,n)
return(echa,faesel)
}


#function to estimate and print the results
calculate<-function(data){
dataset<-createdata(data, niter)
coeffaKohn<-rep(0, niter)
coeffbKohn<-rep(0, niter)
niterKohn<-0
coeffaEggert<-rep(0, niter)
coeffbEggert<-rep(0, niter)
niterEggert<-0

draw<-array(0,c(niter+1, dataset$faesel))
draw1<-array(0,c(niter+1, dataset$faesel))
draw2<-array(0,c(niter+1, dataset$faesel))
draw3<-array(0,c(niter+1, dataset$faesel))

for (k in 1:niter) {
w<-rep(0,dataset$faesel)
w<-w+concent(sample(dataset$echa,dataset$faesel,replace=F))
faesel<-length (w)
dxy<-cbind.data.frame(1:faesel,w)
names(dxy)<-c("x","y")

draw[k,1:faesel]<-w[1:faesel]

ok<-0
while(ok<5){
tmp1<-NA
tmp2<-NA
tmp<-try(coef(nls1<-nls(y~a*x/(b+x), data=dxy,
start=list(a=max(dxy$y),b=1))))
tmp1<-tmp [1]
tmp2<-tmp [2]
if (is.character(tmp1)) {coeffaKohn[k]<-NA
ok<-ok+1}
else {coeffaKohn[k]<-tmp1
niterKohn<-niterKohn + 1
draw1[k,1:faesel]<-predict(nls1)
ok<-5}
if (is.character(tmp2)) {coeffbKohn[k]<-NA}
else {coeffbKohn[k]<-tmp2}
}

ok<-0
while(ok<5){
tmp1<-NA
tmp2<-NA
tmp<-try(coef(nls3<-nls(y~a*(1-exp(b*x)), data=dxy,
start=list(a=max(dxy$y),b=-1))))
tmp1<-tmp [1]
tmp2<-tmp [2]
if (is.character(tmp1)) {coeffaEggert[k]<-NA
ok<-ok+1}
else {coeffaEggert[k]<-tmp1
niterEggert<-niterEggert + 1
draw3[k,1:faesel]<-predict(nls3)
ok<-5}
if (is.character(tmp2)) {coeffbEggert[k]<-NA}
else {coeffbEggert[k]<-tmp2}
}
}

x11()
plot(draw[1,], main="Number of unique genotypes against number of feces
analysed", sub="observed= circles; mean of observed= black line; Kohn's eq=
red line; Eggert's eq= blue line", xlab="Number of feces analysed",
ylab="Number of unique genotypes")
for (k in 2:niter) {
lines(draw[k,], type="o")}
for (k in 1:faesel) {
draw[niter+1,k]<-mean(draw[1:niter,k])
draw1[niter+1,k]<-mean(draw1[1:niter,k])
draw2[niter+1,k]<-mean(draw2[1:niter,k])
draw3[niter+1,k]<-mean(draw3[1:niter,k])
}
lines(draw[niter+1,], type="l", col="black", lwd=2)
lines(draw1[niter+1,], type="l", col="red", lwd=2)
lines(draw3[niter+1,], type="l", col="blue", lwd=2)

minaKohn<-min(coeffaKohn, na.rm=TRUE)
maxaKohn<-max(coeffaKohn, na.rm=TRUE)
meanaKohn<-mean(coeffaKohn, na.rm=TRUE)
sdaKohn<-sd(coeffaKohn, na.rm=TRUE)
minbKohn<-min(coeffbKohn, na.rm=TRUE)
maxbKohn<-max(coeffbKohn, na.rm=TRUE)
meanbKohn<-mean(coeffbKohn, na.rm=TRUE)
sdbKohn<-sd(coeffaKohn, na.rm=TRUE)
minaEggert<-min(coeffaEggert, na.rm=TRUE)
maxaEggert<-max(coeffaEggert, na.rm=TRUE)
meanaEggert<-mean(coeffaEggert, na.rm=TRUE)
sdaEggert<-sd(coeffaEggert, na.rm=TRUE)
minbEggert<-min(coeffbEggert, na.rm=TRUE)
maxbEggert<-max(coeffbEggert, na.rm=TRUE)
meanbEggert<-mean(coeffbEggert, na.rm=TRUE)
sdbEggert<-sd(coeffbEggert, na.rm=TRUE)

pop<-""

cat(pop,niterKohn, minaKohn, meanaKohn, maxaKohn, sdaKohn, sep="  ", file =
"Param_a_Kohn.txt",append=TRUE, fill = TRUE)
cat(pop,niterKohn, minbKohn, meanbKohn, maxbKohn, sdbKohn, sep="  ", file =
"Param_b_Kohn.txt",append=TRUE, fill = TRUE)

cat(pop,niterEggert, minaEggert, meanaEggert, maxaEggert, sdaEggert, sep=" 
", file = "Param_a_Eggert.txt",append=TRUE, fill = TRUE)
cat(pop,niterEggert, minbEggert, meanbEggert, maxbEggert, sdbEggert, sep=" 
", file = "Param_b_Eggert.txt",append=TRUE, fill = TRUE)
x11()
hist1<<-hist(rawdata, right=FALSE, 1:(max(rawdata)+1), plot=FALSE)
hist(rawdata, 1:(max(rawdata)+1), ylim=c(0,(max(hist1$counts)+1)),
right=FALSE, labels = as.character(hist1$mids-0.5), plot=TRUE,
main="Histogram of capture frequencies per sample", xlab="Number of capture
per sample", proba=F)
lines(density(rawdata, 1))
}


i<-1
calculate(rawdata<-scan("Rarefaction_Polana_20081.txt"))


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