hohenTp<- read.table("C:/CLIM/HohenT.txt",header=T)         ###

attach(hohenTp)
quot<- "Hohenpeissenberg, Temperature, 1781-2010";  quot
 
plotAcf<- function(ACF,maxl,cylim,b1,bm){   #Needle-Plot of ACF
plot(1:maxl,ACF,pch=16,ylim=cylim,xlab="lag",
          ylab="Auto-correlation")
for (i in 1:maxl){                                   
  segments(i,0.0,i,ACF[i])}                            #Needles
abline(h=0,lty=3); abline(h=c(-b1,-bm,b1,bm),lty=2)     #Bounds
text(maxl+0.1,b1+0.01,"b1",cex=0.7)
text(maxl+0.1,bm+0.01,"b ",cex=0.7)
text(maxl+0.25,bm+0.01,maxl,cex=0.7)
}

#Vector Y is the time series to be analyzed
Y<- Tyear/100; n<- length(Y);         maxl<- 12    #maximal lag

subtxt<- "Auto-correlation function of time series"; subtxt   
zacf<- acf(Y,lag.max=maxl,type="corr",plot=F)          #no Plot

ACF<-zacf$acf[2:(maxl+1)]; ACF       #Output of $r(1)...r(maxl)
 
postscript(file="C:/CLIM/Acf.ps",height=20,width=12,horiz=F)
par(mfrow=c(2,1))
 
cylim<- c(-0.2,0.33)    
b1<- qnorm(0.975)/sqrt(n);    bm<- qnorm(1-0.025/maxl)/sqrt(n) 
plotAcf(ACF,maxl,cylim,b1,bm)             #Produce Needle-Plot
title(main=quot);  title(sub=subtxt,cex=0.7)

#---Analogously for the detrended series---------------------- 

dev.off()

detach(hohenTp)                                            ###
rm(list=objects())                                         ###