R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(122.27,124.69,147.56,120.03,136.01,138.16,122.87,112.22,137.35,139.08,139.64,121.12,132.37,130.69,149.41,130.72,139.14,146.55,137.35,122.73,138.97,154.73,143.4,123.88,140.25,142.39,143.81,153.58,144.71,153.84,151.3,121.92,153.05,149.29,118.81,109.19,103.68,106.94,114.43,107.87,103.14,117.02,112.44,95.85,123.86,121.83,121.95,120.34,113.32,117.31,141.69,130.35,127.28,148.1,131.21,120.37,146.91,144.04,141.77,132.15,142.04,149.77,172.31,150.24,163.23,155.92,146.96,134.51,152.83,150.54,150.98,138.82)
> 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/1vpt51363703260.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/2la431363703260.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/3ilkt1363703260.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 -0.32742751 -0.25208088  0.10729291  0.13595435 -0.15873923
 [7]  0.18504859 -0.22588419  0.23550598  0.01496253 -0.32504887 -0.08982722
[13]  0.56041321 -0.20819388 -0.20652108  0.04269199  0.07033936 -0.04020724
[19]  0.05640755 -0.14520490  0.21725120 -0.05801632 -0.25471325  0.02530771
[25]  0.29141879 -0.06214423 -0.16755641 -0.06879907  0.12481536 -0.02329015
[31]  0.02947691 -0.09150895  0.15824652 -0.01449928 -0.16123426 -0.03851077
[37]  0.26115244 -0.01870957 -0.12549912 -0.03968923  0.12147117 -0.06124275
[43]  0.05000622 -0.05922477  0.07850379 -0.01449123 -0.06500246 -0.10349724
[49]  0.26341643
> (mypacf <- c(rpacf$acf))
 [1] -0.327427507 -0.402434117 -0.187422273  0.012199774 -0.105567877
 [6]  0.207586353 -0.178882111  0.254796099  0.124515188 -0.274786535
[11] -0.367547004  0.192681563  0.188153801 -0.035065537 -0.112695187
[16] -0.132859810 -0.023500136  0.008804396 -0.007040549 -0.002520131
[21] -0.131631906 -0.053088562 -0.020780983 -0.115000309  0.028318704
[26] -0.066432145 -0.152083732 -0.078145387 -0.125808697  0.085902241
[31] -0.081111382 -0.043570497  0.038951887  0.034385663 -0.045423888
[36] -0.081317312 -0.067713125 -0.061497573  0.073445079  0.078317180
[41] -0.112693101 -0.073291671 -0.035540205  0.001805056 -0.138525519
[46] -0.008074514 -0.038565178  0.022774558
> 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/4390k1363703260.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/57pdj1363703260.tab") 
> 
> try(system("convert tmp/1vpt51363703260.ps tmp/1vpt51363703260.png",intern=TRUE))
character(0)
> try(system("convert tmp/2la431363703260.ps tmp/2la431363703260.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ilkt1363703260.ps tmp/3ilkt1363703260.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.888   0.290   2.160