R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(70.3,90.2,107.3,104.6,102.7,124.5,117.8,104.2,99.9,91.5,95.7,91.4,86.2,91.5,115.5,113.9,131.9,121.2,105.2,107.5,113.8,100.5,104.8,103.8,93.1,106.2,117.5,109.9,123.6,139.3,111,122,110.9,108,103.7,107.3,92,83.4,110.7,109,121.3,121.4,129.9,109.7,113.1,109.4,101,109,92.8,91.1,114.5,118.6,120.2,135.9,122.8,106,118.1,108.9,97.3,113.9,88.3,88.3,114.6,118.8,111.9,130.1,124.3,112.2,110,105.8,105.1,106.7)
> 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/1l61x1489741729.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/2fclh1489741729.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/3oajb1489741729.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 -0.188597385 -0.160367524  0.309657903 -0.200370057
 [6] -0.329404775  0.236461969 -0.228148052 -0.356720424  0.379423438
[11] -0.167132610  0.001015071  0.411595465  0.074715053 -0.102411607
[16]  0.230501566 -0.193118017 -0.218830723  0.086649849 -0.055491099
[21] -0.243087820  0.135953329 -0.044818253 -0.062189440  0.334466389
[26]  0.100785853 -0.093941430  0.089581746  0.097083678 -0.343384666
[31]  0.107972086 -0.009042019 -0.274323932  0.076955886  0.097818540
[36] -0.201822153  0.183603781  0.274315874 -0.163696448  0.086724611
[41]  0.069822505 -0.194547818  0.006515468  0.026247080 -0.201749601
[46]  0.057828134  0.021982490 -0.075855475  0.130290371
> (mypacf <- c(rpacf$acf))
 [1] -0.188597385 -0.203162790  0.254105878 -0.140476148 -0.348741416
 [6]  0.010581545 -0.232813351 -0.402399811  0.032330730 -0.287896390
[11]  0.061821559  0.103322700  0.183519245  0.168652310  0.022853583
[16] -0.091548404 -0.007995633 -0.151648305  0.286321552 -0.081822571
[21]  0.102757761 -0.128947826 -0.130892113  0.125038625  0.048802685
[26] -0.055149707  0.058705429  0.060180431 -0.003915126  0.011841438
[31]  0.021952230 -0.088509532  0.001672953 -0.003149638 -0.063718959
[36] -0.010135242 -0.014451926  0.036417551 -0.108636530 -0.112830018
[41]  0.112460372 -0.048848254 -0.103999360  0.071196225  0.010300248
[46]  0.053070416 -0.007375074  0.032195967
> 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/4xty51489741729.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/5294y1489741729.tab") 
> 
> try(system("convert tmp/1l61x1489741729.ps tmp/1l61x1489741729.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fclh1489741729.ps tmp/2fclh1489741729.png",intern=TRUE))
character(0)
> try(system("convert tmp/3oajb1489741729.ps tmp/3oajb1489741729.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.272   0.132   1.431