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 = '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/1wud31489741317.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/26a2p1489741317.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/3frya1489741317.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  0.477744998  0.191689333  0.107943523 -0.269187371
 [6] -0.468039547 -0.292329865 -0.355478480 -0.255185512  0.159925638
[11]  0.197066745  0.397562442  0.583304835  0.375954057  0.113634052
[16]  0.023882690 -0.282308803 -0.354387423 -0.256960675 -0.290035190
[21] -0.268043548 -0.003026447  0.092717746  0.239962513  0.441507048
[26]  0.302243338  0.110397811  0.042140793 -0.132994325 -0.354379411
[31] -0.206673069 -0.251017918 -0.252629681 -0.039546551  0.092853264
[36]  0.117420847  0.340500333  0.346639023  0.070547237  0.032165133
[41] -0.091982630 -0.240411690 -0.211525929 -0.158530632 -0.198047096
[46] -0.043882544  0.045068965  0.084037830  0.216004318
> (mypacf <- c(rpacf$acf))
 [1]  0.477744998 -0.047360531  0.045003453 -0.431421900 -0.257135160
 [6]  0.077998940 -0.215942404 -0.017670259  0.228837516 -0.062039010
[11]  0.388600240  0.134250890  0.055723961 -0.028199108 -0.052011633
[16] -0.017234755  0.142127576 -0.066730873  0.016129939 -0.336958174
[21] -0.023531850 -0.112851867  0.085639151  0.096118141 -0.061867509
[26] -0.104359205  0.116268067 -0.012641353 -0.022075932  0.100185360
[31] -0.054905370  0.052789453  0.020105197 -0.046906028 -0.057460381
[36]  0.003076889  0.100079382 -0.099069365 -0.052918313  0.002785383
[41]  0.024378585 -0.034323193  0.044971238  0.037138780 -0.036276086
[46] -0.052969937 -0.002278376 -0.040266237
> 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/4zr881489741317.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/5m4e91489741317.tab") 
> 
> try(system("convert tmp/1wud31489741317.ps tmp/1wud31489741317.png",intern=TRUE))
character(0)
> try(system("convert tmp/26a2p1489741317.ps tmp/26a2p1489741317.png",intern=TRUE))
character(0)
> try(system("convert tmp/3frya1489741317.ps tmp/3frya1489741317.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.239   0.146   1.406