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(100.55,100.41,100.54,100.66,100.86,100.88,100.88,101.37,101.84,102.25,102.58,102.59,102.59,101.95,101.94,102.18,102.47,102.5,102.5,102.87,103.08,103.47,103.65,103.68,99.76,99.13,99.19,99.37,99.61,99.65,99.66,99.98,100.38,100.92,101.16,101.19,101.52,101.14,101.38,101.46,101.52,101.53,100.79,101.2,101.28,101.59,101.75,101.76,103.03,102.97,103.11,103.17,103.17,103.2,102.17,102.22,102.18,102.44,102.61,102.63)
> 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/1komx1483009143.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/2hhl51483009143.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/3q9s21483009143.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  0.854670853  0.668716578  0.482986597  0.328418058
 [6]  0.202573440  0.079214182 -0.022713527 -0.110170589 -0.153392230
[11] -0.149893866 -0.138194138 -0.153133305 -0.181259951 -0.245809866
[16] -0.292638756 -0.316240905 -0.313057998 -0.302930996 -0.329787224
[21] -0.336408503 -0.322826878 -0.275381478 -0.209012404 -0.143591927
[26] -0.085155188 -0.045931183 -0.002800088  0.045486117  0.094922518
[31]  0.124662387  0.105939874  0.089742124  0.083069844  0.103646584
[36]  0.139475143  0.183210616  0.176087896  0.161595230  0.148540823
[41]  0.136307511  0.120130050  0.088990428  0.046304819  0.006400769
[46] -0.026283751 -0.047580557 -0.063503389 -0.080129677
> (mypacf <- c(rpacf$acf))
 [1]  0.854670853 -0.229079948 -0.092738113 -0.005423880 -0.033254696
 [6] -0.123833116 -0.025287619 -0.063452060  0.052034284  0.066858527
[11] -0.051669027 -0.139480313 -0.049208301 -0.198877443 -0.008532117
[16] -0.016352655  0.004084558 -0.049263448 -0.187919573 -0.007870984
[21] -0.037197639 -0.002227652 -0.004530161  0.003836327  0.002065703
[26] -0.058437110  0.003268055 -0.026287585  0.018812894 -0.030456922
[31] -0.157105283  0.082299083 -0.025832819  0.044669806  0.012197235
[36]  0.071029902 -0.160103534  0.026994991 -0.002564328 -0.052370763
[41]  0.003394825 -0.004778427 -0.048969922  0.083019446 -0.086576974
[46] -0.033576320 -0.058353229  0.017622785
> 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/4dc0n1483009143.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/5b5eb1483009143.tab") 
> 
> try(system("convert tmp/1komx1483009143.ps tmp/1komx1483009143.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hhl51483009143.ps tmp/2hhl51483009143.png",intern=TRUE))
character(0)
> try(system("convert tmp/3q9s21483009143.ps tmp/3q9s21483009143.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.249   0.102   1.368