R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(94.9,95.8,98.8,100.6,100.6,100.1,99.4,99.9,101,100.4,101.6,106.8,109.3,112.6,118.8,121.9,118.3,117.9,119.2,116.3,119.2,118.7,120.3,120.5,124.3,128.3,131.4,130.3,126.6,121.8,125.1,128.5,129.5,128.5,127.2,126.2,125.9,127.3,125.7,122.5,121.3,121.5,123.4,121.6,121.8,118.9,118.7,119.8,118.5,118.9,117.4,116,115.5,116.5,114.9,113.9,114.3,112,108,97.7)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/1ws271452255207.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/23sv11452255207.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/3mctk1452255207.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]  1.000000000  0.352909848  0.061109942 -0.047415933  0.011093528
 [6]  0.057580126  0.116070219  0.095308106 -0.052517637  0.056524493
[11]  0.203611588  0.278730566  0.220772061  0.066566888 -0.065340948
[16] -0.103248030  0.084793712  0.010571898  0.004000283  0.070039570
[21]  0.079058619 -0.016258891  0.059179665  0.084995054  0.013131329
[26] -0.098736786 -0.102014581 -0.117684045 -0.127350551  0.017779137
[31]  0.113532604  0.025974111 -0.071753944 -0.155558621 -0.167073588
[36] -0.103318548 -0.055981360 -0.147129039 -0.019981999 -0.052901748
[41]  0.017515176 -0.044812089  0.011537809 -0.019807862 -0.173251620
[46] -0.184994971 -0.135899304 -0.128979696 -0.149109111
> (mypacf <- c(rpacf$acf))
 [1]  0.352909848 -0.072459973 -0.051642269  0.057937541  0.040505119
 [6]  0.086430132  0.031474390 -0.109376057  0.144238243  0.171337861
[11]  0.149859597  0.092735415 -0.029881130 -0.063948705 -0.065402318
[16]  0.104351550 -0.133565205 -0.001206397  0.108237994  0.003485502
[21] -0.130071706  0.028637257 -0.010628529  0.010795506 -0.105387453
[26] -0.048895805 -0.065471478 -0.097231169  0.057553293  0.087722292
[31] -0.051072029 -0.089287644 -0.101142559 -0.087048451 -0.052906509
[36] -0.030498584 -0.036165065  0.186327198 -0.060592604  0.047189636
[41] -0.096321686  0.014928404  0.054581327 -0.066896973 -0.050354732
[46] -0.009473232 -0.065650729 -0.081478663
> 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/4vfc11452255207.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/57cj11452255207.tab") 
> 
> try(system("convert tmp/1ws271452255207.ps tmp/1ws271452255207.png",intern=TRUE))
character(0)
> try(system("convert tmp/23sv11452255207.ps tmp/23sv11452255207.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mctk1452255207.ps tmp/3mctk1452255207.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.232   0.256   1.493