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(2.04,2.08,1.94,1.91,1.34,1.3,1.39,1.23,1.3,1.79,2.25,2.63,2.8,3.08,3.89,3.68,4.62,5.07,5.22,4.94,5.14,4.8,3.89,3.54,3.34,2.8,1.6,1.56,0.68,-0.11,-0.66,-0.2,-0.62,-0.59,-0.3,-0.26,-0.08,0.13,0.94,1.05,1.59,2.03,2.15,2.05,2.56,2.54,2.53,2.6,2.71,2.82,2.92,2.87,2.89,3.27,3.32,3.14,3.04,3.09,3.39,3.24,3.38,3.41,3.14,2.96,2.74,2.21,2.24,2.56,2.39,2.49,2.17,2.16,1.48,1.09,1.25,1.27,1.39,1.69,1.55,1.19,1.08,0.94,0.98,1.01)
> 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/1op851413725950.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/2g8xh1413725950.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/3uh9r1413725950.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  0.342643706  0.341096001  0.379660895  0.338944717
 [6] -0.021744780  0.076616085  0.193713262 -0.089875375 -0.194015595
[11] -0.227314525 -0.173056741 -0.611807764 -0.245895955 -0.261390767
[16] -0.262745230 -0.306223863 -0.070407061 -0.143807390 -0.160524470
[21] -0.028979388 -0.024826317  0.087507825 -0.004416206  0.100828133
[26]  0.032866561  0.059402858  0.034034014  0.036832394  0.027864299
[31]  0.049129749 -0.029343892 -0.068129000  0.071835347 -0.059058051
[36]  0.004732397  0.078459372  0.050783649  0.005004941  0.040969637
[41]  0.084883263 -0.011384237  0.073865617  0.108005496  0.136470769
[46] -0.037177301  0.041317210  0.048613150 -0.054056077
> (mypacf <- c(rpacf$acf))
 [1]  0.342643706  0.253447184  0.248898853  0.149419350 -0.345928385
 [6] -0.082410006  0.211595034 -0.138352195 -0.212775728 -0.350983585
[11] -0.022098076 -0.384406058  0.245519523  0.058800539  0.050995131
[16]  0.004187351 -0.054116399 -0.020219264  0.143286911 -0.059747062
[21] -0.263047824 -0.067943969 -0.065321339 -0.344836460  0.095695684
[26] -0.096154683  0.092772678 -0.055540661  0.066780547 -0.023455057
[31] -0.020989108 -0.090084230  0.024292489 -0.030512439  0.019037811
[36] -0.162902617 -0.097293022 -0.071613134  0.058862096 -0.098149980
[41] -0.027978199  0.044170516  0.039481116  0.014230087 -0.033402069
[46] -0.196437585  0.074214024  0.006630461
> 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/4m2nz1413725950.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/5wqgb1413725950.tab") 
> 
> try(system("convert tmp/1op851413725950.ps tmp/1op851413725950.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g8xh1413725950.ps tmp/2g8xh1413725950.png",intern=TRUE))
character(0)
> try(system("convert tmp/3uh9r1413725950.ps tmp/3uh9r1413725950.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.155   0.198   1.368