R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(101.74,100.73,100.86,100.78,100.76,100.77,100.77,101.93,101.98,102.47,102.59,102.54,102.54,101.29,101.49,101.71,101.98,102.11,102.11,103.13,103.43,103.8,103.99,104.03,104.03,102.58,102.65,102.81,102.98,103.12,103.12,104.33,104.41,104.66,104.81,104.9,100.15,98.74,98.74,98.96,99.34,99.4,99.5,100.5,100.77,101.08,101.39,101.43,101.43,101.29,101.33,101.15,101.25,101.13,101.07,101.33,101.61,101.29,101.39,101.46,101.81,101.78,101.93,102.01,102.03,102.14,101.81,101.52,101.38,101.5,101.65,101.64)
> 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/10tdl1489660184.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/2djtt1489660184.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/339p21489660184.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  0.206632919  0.019219943 -0.063801525 -0.084241124
 [6] -0.158592584 -0.280197052 -0.150286400 -0.092838949 -0.060282113
[11] -0.016389208  0.195334914  0.270674636  0.047586651 -0.001054850
[16] -0.022004751 -0.065457570 -0.101295670 -0.188095412 -0.058482332
[21] -0.079056894  0.006097826 -0.021758382  0.139710682  0.132121455
[26]  0.032233259 -0.020610382 -0.072532687 -0.022473461 -0.129263180
[31] -0.062402899  0.036361503  0.017835810 -0.011145054 -0.023113067
[36]  0.112855890  0.081419167  0.007773474  0.006414842  0.005079657
[41]  0.001290596  0.027810164 -0.028385125 -0.002247001 -0.003934389
[46] -0.015873434 -0.001932912 -0.022332189  0.004642584
> (mypacf <- c(rpacf$acf))
 [1]  0.206632919 -0.024524340 -0.065643443 -0.059908038 -0.135427198
 [6] -0.241717439 -0.073546256 -0.092335957 -0.100828388 -0.073347853
[11]  0.128042313  0.131276372 -0.099417565 -0.036787290 -0.031201766
[16] -0.064640445 -0.011180306 -0.103624764 -0.006784238 -0.085106013
[21]  0.010371406 -0.112119810  0.025299957 -0.014775349 -0.041820020
[26] -0.085156180 -0.094533364 -0.030268057 -0.115234234 -0.012831245
[31]  0.028107919 -0.047730198 -0.083288607 -0.096916781 -0.011465760
[36] -0.048162243 -0.035924269 -0.018379833 -0.013478986 -0.036790240
[41]  0.101949614 -0.090673988 -0.032455108 -0.007255825 -0.009187857
[46] -0.019850320 -0.100793789 -0.012287846
> 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/48dsv1489660184.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/5g83f1489660184.tab") 
> 
> try(system("convert tmp/10tdl1489660184.ps tmp/10tdl1489660184.png",intern=TRUE))
character(0)
> try(system("convert tmp/2djtt1489660184.ps tmp/2djtt1489660184.png",intern=TRUE))
character(0)
> try(system("convert tmp/339p21489660184.ps tmp/339p21489660184.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.292   0.115   1.436