R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(111.2,116.7,125.8,131.5,146.2,155.4,157.5,137.2,121.3,89.1,69.6,56.7,58.5,56.4,60.5,64.6,73.2,84.6,80.4,88.4,84.6,90.8,94.9,93.1,96.6,93.1,98.3,105,95.6,94.3,95.3,97.1,98.1,104.4,107.8,114.3,118.7,124.1,134.2,142.4,133.8,131,133.2,125.9,126.2,122.7,126.6,124.8,128,134.1,138.8,134,124,110.4,116.7,124.7,126,122.8,120.2,121.2,125.4,127.9,122,117.5,117.9,117.9,122.7,125.7,126.1,123.2,120.6,123.5)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/1uzbz1413633046.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2gegv1413633046.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3g4ka1413633046.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.94102980  0.82265475  0.66760184  0.51086017  0.36858232
 [7]  0.25127988  0.16818835  0.11947121  0.10064394  0.09645276  0.09299828
[13]  0.08043471  0.06107095  0.04100791  0.03017449  0.01845133  0.00362171
[19] -0.01616354 -0.03856476 -0.06976018 -0.10839800 -0.15384656 -0.20627905
[25] -0.25570873 -0.28894883 -0.31403322 -0.31272979 -0.29707533 -0.26806638
[31] -0.23354373 -0.19429297 -0.15695261 -0.13105745 -0.12322731 -0.13078095
[37] -0.14194029 -0.14960574 -0.15064970 -0.14700423 -0.13035123 -0.10833604
[43] -0.08012061 -0.05936474 -0.05061483 -0.06215813 -0.07806653 -0.08966826
[49] -0.09417531
> (mypacf <- c(rpacf$acf))
 [1]  0.941029801 -0.549368656 -0.185919819  0.124188477  0.019119062
 [6] -0.001228983  0.096563966  0.048964397  0.013575638 -0.074773990
[11] -0.074867060 -0.044300140  0.049887207  0.065415129  0.094162296
[16] -0.147068221 -0.077935940 -0.015103101 -0.019216971 -0.128894140
[21] -0.013127109 -0.013480280 -0.106503611 -0.013232643  0.091522404
[26] -0.202229771  0.214092714 -0.051253014 -0.052841375 -0.018372467
[31]  0.084073350 -0.048995172 -0.068841007 -0.116280600  0.051714989
[36]  0.067476038  0.004347773 -0.038942814  0.013951879  0.044788107
[41] -0.022648433 -0.018717484 -0.133388669 -0.070418805  0.003089621
[46]  0.097938223 -0.026779607 -0.054480443
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 2:(par1+1)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-1,header=TRUE)
+ a<-table.element(a,round(myacf[i],6))
+ mytstat <- myacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/47m8f1413633046.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:par1) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(mypacf[i],6))
+ mytstat <- mypacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5x8ox1413633046.tab") 
> 
> try(system("convert tmp/1uzbz1413633046.ps tmp/1uzbz1413633046.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gegv1413633046.ps tmp/2gegv1413633046.png",intern=TRUE))
character(0)
> try(system("convert tmp/3g4ka1413633046.ps tmp/3g4ka1413633046.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.152   0.179   1.343