R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(75.8,75.7,112.3,110.9,99.6,107.5,90,88.8,129.7,120.4,93.3,96,81.1,78,111.9,117.6,101,98.3,91,86.8,108.8,110.1,93.8,100.6,75.7,69,116,94.5,105.1,95.3,79.7,76.1,111.1,106.3,89.5,96.8,67.8,62.5,90.1,93.6,94.2,93.2,81,73.7,97.7,97.5,82.7,88.8,68.5,61.1,89.6,87.6,90.8,84.3,75,78.4,83.5,93,79.3,83.9,65,60.3,80.6,86.5,78.7,80.7,70.6,67.2,88,89.1,69,84.1)
> 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. 1.2.327 (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/1q5lj1476809766.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/224r21476809766.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/3zk4m1476809766.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  0.418373720  0.041386985  0.102388572 -0.014413556
 [6]  0.306471789  0.703154683  0.310518237 -0.067111324  0.020220944
[11] -0.033557861  0.243865058  0.650771193  0.285774337 -0.026860995
[16] -0.038518211 -0.157419158  0.112472680  0.444454592  0.145569035
[21] -0.114782606 -0.085199791 -0.198335327  0.041545928  0.415963163
[26]  0.111496075 -0.113231305 -0.118780588 -0.258449164 -0.056770786
[31]  0.204322781  0.019549345 -0.198981691 -0.169749944 -0.259098964
[36] -0.124156928  0.158145830  0.005711873 -0.183862336 -0.169634473
[41] -0.243303617 -0.154786448  0.034959608 -0.070021308 -0.216240926
[46] -0.184831942 -0.229245288 -0.141653068  0.015358679
> (mypacf <- c(rpacf$acf))
 [1]  0.418373720 -0.162006678  0.186786242 -0.174093106  0.540259629
 [6]  0.466537763 -0.167555049 -0.285304438  0.131970608  0.005225721
[11]  0.154382260  0.201453690 -0.073006000  0.068769630 -0.206417354
[16] -0.225472446 -0.027010697 -0.046762889 -0.085988405  0.040134982
[21]  0.107091322 -0.013226597 -0.056928903  0.072319045 -0.097507137
[26] -0.001485093 -0.091898799  0.048920134 -0.035247005 -0.207870141
[31]  0.071240677 -0.071814495  0.053750230 -0.028365960 -0.077293928
[36]  0.016150633  0.054456769 -0.173334821  0.115145126  0.095807414
[41] -0.045849211 -0.113104668 -0.042538901  0.044180986 -0.035944658
[46] -0.078941730  0.130165519 -0.027623185
> 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/42w7b1476809766.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/59qhj1476809766.tab") 
> 
> try(system("convert tmp/1q5lj1476809766.ps tmp/1q5lj1476809766.png",intern=TRUE))
character(0)
> try(system("convert tmp/224r21476809766.ps tmp/224r21476809766.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zk4m1476809766.ps tmp/3zk4m1476809766.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.299   0.112   1.433