R version 3.2.2 (2015-08-14) -- "Fire Safety"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(88.52,90.15,88.63,88.32,88.51,88.53,88.35,88.4,88.41,88.47,88.46,89.28,89.11,90.74,89.49,88.62,89.09,89.14,89.45,89.33,89.44,89.54,89.52,90.48,90.04,91.93,91.25,89.27,90.57,90.79,90.83,90.76,91.29,91.48,91.63,92.63,91.7,93.86,92.45,92.03,92.71,93.15,92.98,92.73,93.29,93.2,93.34,93.95,93.43,95.67,94.02,93.51,94.6,94.27,94.05,94.1,94.51,94.53,94.2,93.58,94.94,96.24,95.77,94.41,95.09,95.37,95.17,95.05,95.33,95.42,95.95,96.12,96.94,98.73,98.03,97.42,98.39,98.77,98.46,98.3,98.25,98.33,98.61,98.99,98.8,100.26,100.85,98.87,99.81,100.44,100.07,99.8,99.77,99.9,100.58,100.86,101.05,101.3,101.45,101.13,101.38,101.03,100.79,100.84,101.17,101.36,101.14,101.24)
> 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. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) 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)
> 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/1wqgs1445624339.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/2b23d1445624339.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/37kik1445624339.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 -0.312583070 -0.245933048  0.127181328  0.006844750
 [6]  0.038938175 -0.114981951 -0.008675315 -0.008422473  0.128492565
[11] -0.195635308 -0.231255447  0.691834509 -0.149098264 -0.266277196
[16]  0.096002610  0.038590139  0.009555947 -0.114422984  0.009581762
[21] -0.038603886  0.154110813 -0.210064532 -0.171698232  0.543158110
[26] -0.111209641 -0.211479902  0.057223806  0.058908740  0.006420159
[31] -0.103525275 -0.008921732  0.023904380  0.046184872 -0.104271795
[36] -0.205372567  0.446763926 -0.067338841 -0.180664964  0.116595842
[41]  0.009656096 -0.018441284 -0.026574549 -0.016149405  0.040056358
[46]  0.042488724 -0.167601140 -0.101832524  0.340975282
> (mypacf <- c(rpacf$acf))
 [1] -0.312583070 -0.380853748 -0.127064660 -0.104058321  0.036540503
 [6] -0.109551291 -0.088189433 -0.159955764  0.059462169 -0.207953256
[11] -0.452175632  0.469551216  0.280394560  0.094480041  0.014870385
[16]  0.006830892 -0.107326871 -0.161685556 -0.023510415 -0.055159623
[21]  0.058911624 -0.105912985 -0.087606464  0.016626220 -0.082838082
[26] -0.006085391  0.010215198  0.014662073 -0.012735983 -0.008395068
[31] -0.071772162  0.084362793 -0.170478514  0.036159511 -0.152191987
[36] -0.061029049 -0.118940939 -0.020776643  0.182199653  0.053983627
[41] -0.033704358  0.046377878  0.061257145  0.019364809  0.123363502
[46] -0.093154593  0.039188366 -0.029629762
> 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/49uxc1445624339.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/5frkx1445624339.tab") 
> 
> try(system("convert tmp/1wqgs1445624339.ps tmp/1wqgs1445624339.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b23d1445624339.ps tmp/2b23d1445624339.png",intern=TRUE))
character(0)
> try(system("convert tmp/37kik1445624339.ps tmp/37kik1445624339.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.152   0.225   1.384