R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(78.7,75.7,77.1,86.1,86.8,86.3,91.5,90.7,78.2,73,73.7,77.3,67.5,72.7,76.6,82.4,82.3,86.3,93,88.8,96.9,103.9,115.7,112.8,114.7,118,129.3,137,156,166.2,167.8,144.3,126,90.4,67.5,52.4,54.6,52.9,59.1,63.3,73.8,87.6,81.8,90.7,86.3,93.6,98,94.3,97.6,94.2,100.2,106.7,95.7,94.6,94.7,96.2,96.3,103.3,106.8,113.7,117.4,123.6,137.6,147.4,137.2,133.8,136.7,127.3,128.7,127,133.7,132,135.1,142.6,149.3,143.5,131.4,114.7,122.3,133.4,134.6,130.9,127.9,128,133.3,136.3,129.5,124.6,125.5,126.2,133.3,137,137.8,133.5,129.9,133.3)
> 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/1i2jz1425291078.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/2c6ps1425291078.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/3fr5p1425291078.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  0.463969291  0.247832876 -0.013702259 -0.064049368
 [6] -0.194721408 -0.243755798 -0.213779793 -0.161764860 -0.158379034
[11] -0.051020874  0.035714462  0.007801100 -0.095311571 -0.136096010
[16] -0.038900063 -0.029157946  0.013374212 -0.019377417  0.039971461
[21] -0.035573426  0.074456788  0.112313050  0.130090894 -0.030604056
[26]  0.061766331 -0.109694622 -0.110410228 -0.126345657 -0.093685747
[31] -0.053497234 -0.074194043  0.018372286  0.161075851  0.139943062
[36]  0.049256354 -0.030767707 -0.039568113 -0.040472850 -0.082114845
[41]  0.014740886  0.007683803  0.081974236  0.083141201  0.168472833
[46]  0.062506858 -0.018060402 -0.074879255 -0.034360362
> (mypacf <- c(rpacf$acf))
 [1]  0.463969291  0.041498693 -0.182760884 -0.004601262 -0.154784309
 [6] -0.130509493 -0.020514459 -0.051758417 -0.115520005  0.044457693
[11]  0.028402682 -0.131636106 -0.164477589 -0.099289630  0.048607464
[16] -0.055466034 -0.011711487 -0.096482048 -0.016376878 -0.129546071
[21]  0.086568719  0.037550923 -0.030567302 -0.144829777  0.153338221
[26] -0.270397451 -0.105533775  0.055262264 -0.107206437 -0.033158386
[31] -0.061903229 -0.026474739  0.080223434 -0.081453846 -0.106479095
[36] -0.092975743 -0.048961991 -0.046673163 -0.059497704 -0.033801107
[41] -0.077093926  0.054131699  0.027634136 -0.070693960 -0.091531658
[46] -0.078651794 -0.026536390  0.021469112
> 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/45dmt1425291078.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/5f6xj1425291078.tab") 
> 
> try(system("convert tmp/1i2jz1425291078.ps tmp/1i2jz1425291078.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c6ps1425291078.ps tmp/2c6ps1425291078.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fr5p1425291078.ps tmp/3fr5p1425291078.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.182   0.215   1.403