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(101.68,101.25,101.24,101.11,101.08,101.09,101.09,101.62,101.66,101.96,102.04,102.02,102.02,101.51,101.62,101.83,102.06,102.14,102.14,102.59,102.92,103.31,103.54,103.58,103.58,102.83,102.86,103.03,103.2,103.28,103.28,103.79,103.92,104.26,104.41,104.45,99.92,99.18,99.18,99.35,99.62,99.67,99.72,100.08,100.39,100.77,101.03,101.07,101.29,101.1,101.2,101.15,101.24,101.16,100.81,101.02,101.15,101.06,101.17,101.22,101.84,101.79,101.88,101.9,101.91,101.96,101.26,101.06,100.98,101.12,101.24,101.25)
> 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/1gxsi1489738814.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/2rkcu1489738814.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/39ple1489738814.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  0.168359153  0.005582588 -0.096520923 -0.085901426
 [6] -0.081408047 -0.094807735 -0.079163467 -0.107203879 -0.104264056
[11] -0.032235870  0.135257156  0.082480541  0.064318396 -0.032177809
[16] -0.052232790 -0.079749070 -0.035575889  0.008128183 -0.053665005
[21] -0.078414120 -0.039198109 -0.037590420  0.058421988 -0.036614638
[26]  0.033833173 -0.015705672 -0.051745368 -0.009029826 -0.049984636
[31]  0.100413351  0.036655015  0.007815190 -0.017671390 -0.020261852
[36]  0.040773033  0.035250780  0.007074334  0.010007452  0.008306890
[41]  0.005503428  0.044761440 -0.006612558  0.002156658 -0.010788495
[46] -0.019080462 -0.008752980 -0.035797936  0.008073256
> (mypacf <- c(rpacf$acf))
 [1]  0.168359153 -0.023426228 -0.096320343 -0.055330150 -0.060629463
 [6] -0.084460208 -0.067253176 -0.108557212 -0.106536715 -0.039529151
[11]  0.105709877 -0.004562442  0.010229396 -0.062417937 -0.054164907
[16] -0.075866914 -0.024528677  0.002927241 -0.068034960 -0.070081442
[21] -0.031627388 -0.088532181  0.011234043 -0.128533614 -0.002726880
[26] -0.063601051 -0.083399890 -0.041687314 -0.120412044  0.066741347
[31] -0.035388441 -0.047079307 -0.044539269 -0.078249980  0.020379783
[36] -0.043694406 -0.031406581 -0.013168441 -0.011251521  0.001425738
[41] -0.014726225 -0.046115997 -0.038925725 -0.022862185 -0.014937360
[46] -0.040646713 -0.044965279 -0.038903668
> 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/4zubl1489738814.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/5ysa31489738814.tab") 
> 
> try(system("convert tmp/1gxsi1489738814.ps tmp/1gxsi1489738814.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rkcu1489738814.ps tmp/2rkcu1489738814.png",intern=TRUE))
character(0)
> try(system("convert tmp/39ple1489738814.ps tmp/39ple1489738814.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.582   0.129   1.802