R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(90.18,90.5,90.63,90.75,90.76,90.67,90.5,90.8,91.22,92.19,92.51,92.67,93.75,94.1,94.96,95.21,95.33,95.43,95.44,95.64,95.8,95.87,95.98,96.07,96.23,96.32,96.55,96.73,96.61,96.64,96.86,97.02,97.22,98.1,98.46,98.6,98.78,99.13,99.48,99.62,99.68,99.95,100.12,100.25,100.47,100.7,100.88,100.95,100.92,101.12,101.19,101.28,101.28,101.3,101.3,101.36,101.45,101.58,101.73,101.84,102.01,102.14,102.16,102.32,102.41,102.4,102.43,102.42,102.3,102.65,102.72,102.86)
> 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/1u37x1457972052.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/2bfry1457972052.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/3wb311457972052.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]  1.00000000  0.95946226  0.91873117  0.87637868  0.83385297  0.78866707
 [7]  0.74034973  0.68906922  0.63791436  0.58837327  0.54498232  0.50237821
[13]  0.45956212  0.42325498  0.38827578  0.35865603  0.33023011  0.30195854
[19]  0.27339763  0.24337073  0.21316924  0.18260555  0.15112106  0.11909156
[25]  0.08685214  0.05342457  0.01896463 -0.01468874 -0.04724177 -0.08082394
[31] -0.11497324 -0.14816282 -0.18019057 -0.21186757 -0.23784600 -0.26060804
[37] -0.28166667 -0.30168081 -0.31962151 -0.33412735 -0.34416513 -0.35335513
[43] -0.36033116 -0.36561166 -0.37033702 -0.37458327 -0.37690711 -0.37748166
[49] -0.37769516
> (mypacf <- c(rpacf$acf))
 [1]  0.959462259 -0.023122368 -0.041645790 -0.024682904 -0.056380357
 [6] -0.064822426 -0.064436342 -0.027898152 -0.008744349  0.049684574
[11] -0.014295367 -0.030771338  0.053516028 -0.014868749  0.031999355
[16] -0.014519175 -0.028852264 -0.032176764 -0.048937437 -0.034468213
[21] -0.035070846 -0.028506869 -0.029016113 -0.021247128 -0.034606862
[26] -0.043260353 -0.013839530 -0.018752360 -0.044691723 -0.043487894
[31] -0.029612742 -0.027453787 -0.040609505  0.029270580  0.003269712
[36] -0.013496270 -0.023557488 -0.018520921  0.001150960  0.017275063
[41] -0.024419815 -0.005455376 -0.001840084 -0.022908591 -0.028309387
[46]  0.002288635  0.002317177 -0.007658986
> 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/4r7zm1457972052.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/5p4721457972052.tab") 
> 
> try(system("convert tmp/1u37x1457972052.ps tmp/1u37x1457972052.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bfry1457972052.ps tmp/2bfry1457972052.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wb311457972052.ps tmp/3wb311457972052.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.372   0.262   1.637