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(100.8,100.9,101.5,101.8,102.3,102.7,103.3,104.3,103.9,104.1,104.5,104,105.3,105.3,105.7,105.7,105.3,105.6,106.5,107,106.6,106.4,105.6,105.8,106.3,105.2,104.1,103.4,102.6,101.6,101.7,101,100.7,100.8,100.3,99.8,100,100.3,100.1,100.8,100.1,99.9,100.5,100.6,99.9,99.5,99.2,98.9,98.8,98.4,98.9,98.4,98.3,98.1,98.2,97.6,96.8,96.6,96,94.9,95.2,95,93.7,92.9,92.3,93.2,89.6,89.2,88.7,88.4,88.9,88.3,85.8,86.8,86.9,85.7,84.5,84,85,85.2,85,84.8,84.5,85)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> 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/13mit1425497033.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/2op3a1425497033.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/3scfe1425497033.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  0.971948153  0.941154473  0.910184429  0.876800599
 [6]  0.840779961  0.800105051  0.752801822  0.706327809  0.662671651
[11]  0.620117631  0.574535524  0.525302022  0.483427516  0.441549766
[16]  0.397163113  0.352691611  0.310285131  0.268828205  0.236852582
[21]  0.201184310  0.167555301  0.136359353  0.110232554  0.084406240
[26]  0.057227024  0.034590028  0.014157488 -0.005175256 -0.022182666
[31] -0.036519580 -0.051683729 -0.067296623 -0.083581824 -0.098331815
[36] -0.114874627 -0.130864568 -0.147567350 -0.165234277 -0.182283841
[41] -0.198345661 -0.212826152 -0.229224306 -0.247849434 -0.265986904
[46] -0.281655284 -0.299231957 -0.317176310 -0.336148941
> (mypacf <- c(rpacf$acf))
 [1]  0.971948153 -0.063791478 -0.016706369 -0.059852530 -0.061754148
 [6] -0.100641079 -0.136996789 -0.002127657  0.029157606  0.006082846
[11] -0.069883426 -0.082750190  0.113575043 -0.049179610 -0.084511098
[16] -0.033732894  0.022947185 -0.016719536  0.113276998 -0.109314366
[21]  0.038757376  0.006754649  0.035664705 -0.073103041 -0.054853623
[26]  0.080073466 -0.009186386 -0.030029139 -0.002390463  0.027321238
[31]  0.005886857 -0.099769946 -0.067823882  0.018550697 -0.027667691
[36] -0.041745230 -0.042988990 -0.024657275  0.033549057 -0.038172124
[41]  0.009637063 -0.068447144 -0.054696568  0.002691551 -0.014195678
[46] -0.061979772 -0.022643959 -0.011893911
> 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/4una91425497033.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/52ysw1425497033.tab") 
> 
> try(system("convert tmp/13mit1425497033.ps tmp/13mit1425497033.png",intern=TRUE))
character(0)
> try(system("convert tmp/2op3a1425497033.ps tmp/2op3a1425497033.png",intern=TRUE))
character(0)
> try(system("convert tmp/3scfe1425497033.ps tmp/3scfe1425497033.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.205   0.212   1.421