R version 3.2.4 (2016-03-10) -- "Very Secure Dishes"
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> x <- c(105.95,108.55,110.81,111.54,110.38,106.67,106.45,105.44,105.37,103.72,106.57,108.54,110.36,106.64,103.45,101.36,101.9,100.86,100.37,100.16,99.5,99.52,99.2,99.35,99.37,99.85,99.76,100.07,99.77,99.93,99.16,99.4,99.81,99.67,99.37,99.49,99.28,99.33,99.19,98.11,99.12,99.06,97.41,98.45,100.33,103.18,103.06,103.48,102.8,103.92,103.9,103.96,103.62,103.83,104.09,104.07,103.22,104.01,104.01,104.24,102.93,104.73,106.48,119.5,122.45,125.29,126.56,126.38,127.95,128.23,128.7,127.86)
> 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/1xnsk1458078576.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/2e7mn1458078576.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/3qcvc1458078576.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  0.329930066  0.215451129 -0.106386518  0.013498031
 [6]  0.011652599 -0.002836730 -0.070942216  0.007879012  0.103407556
[11]  0.046436533 -0.034008524 -0.045346891 -0.019355002  0.035109831
[16] -0.026525930  0.012277233  0.017073491  0.119462586  0.099108891
[21]  0.060557965 -0.020371833 -0.010328352  0.025383107 -0.036911729
[26]  0.004437798 -0.035932453 -0.059712943 -0.007335800 -0.025480480
[31] -0.055136343 -0.064885950 -0.034744156  0.009802227  0.030990912
[36] -0.020087650 -0.041721572  0.003330197 -0.009703916 -0.019029052
[41] -0.078189985 -0.029187599  0.003526925  0.010011597 -0.045486247
[46] -0.040383505 -0.071710334  0.001335440 -0.160443196
> (mypacf <- c(rpacf$acf))
 [1]  0.329930066  0.119618179 -0.237288462  0.102645037  0.060142647
 [6] -0.093713801 -0.057224098  0.099765082  0.110641059 -0.092850549
[11] -0.069977640  0.065809308 -0.004754760 -0.010782262 -0.038774173
[16]  0.071558128  0.024719715  0.052496855  0.051868993  0.005393506
[21] -0.040174210  0.003932830  0.052692453 -0.083835983  0.034474909
[26]  0.005126808 -0.123044306  0.042822999  0.019525594 -0.091290579
[31] -0.030390309  0.032473913  0.036818945 -0.027895220 -0.047678498
[36]  0.005626423  0.028118618 -0.062360972 -0.027860531 -0.008818459
[41]  0.011322064 -0.006266164 -0.023573863 -0.025437012  0.016899879
[46] -0.065158305  0.031303921 -0.191490424
> 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/4kgzl1458078576.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/5kfzy1458078576.tab") 
> 
> try(system("convert tmp/1xnsk1458078576.ps tmp/1xnsk1458078576.png",intern=TRUE))
character(0)
> try(system("convert tmp/2e7mn1458078576.ps tmp/2e7mn1458078576.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qcvc1458078576.ps tmp/3qcvc1458078576.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.205   0.239   1.452