R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(910,910,970,950,980,860,920,950,900,950,950,940,860,810,870,960,970,860,850,910,970,980,970,1000,910,740,810,1050,920,830,880,910,880,960,900,1110,870,720,780,970,1020,830,820,920,840,920,920,1150,820,760,760,960,1010,790,820,880,820,870,870,1230,760,810,850,990,940,850,860,860,780,880,850,1220,850,800,840,1090,810,870,810,860,800,870,860,1220,820,860,750,1020,780,830,860,850,820,790,1020,1230,760,880,760,1090,840,900,930,820,780,870,990,1270)
> 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/15dwk1377051338.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/24a921377051338.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/3p4b51377051338.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 -0.397379162 -0.016281684 -0.300300262  0.348905395
 [6] -0.081852359 -0.094204651 -0.009523341  0.347940852 -0.305385399
[11] -0.070377150 -0.295734144  0.765227055 -0.308937591  0.015067614
[16] -0.293700131  0.373805939 -0.164051948 -0.060841546  0.034188213
[21]  0.296340688 -0.258168978 -0.139616343 -0.158608551  0.585598678
[26] -0.251984080  0.036933870 -0.247808262  0.321642653 -0.172795122
[31] -0.066717654  0.087967014  0.199928685 -0.156893857 -0.200852835
[36] -0.053495192  0.433254235 -0.206284802  0.046350329 -0.173728463
[41]  0.241928521 -0.174096573 -0.044455140  0.115479146  0.128918299
[46] -0.103981894 -0.194315949 -0.001116337  0.291550880
> (mypacf <- c(rpacf$acf))
 [1] -0.397379162 -0.206856658 -0.484220257 -0.040125378 -0.055434533
 [6] -0.256430963 -0.069445872  0.379026402 -0.099176322 -0.140470370
[11] -0.528991535  0.362707481  0.177924294  0.098698992 -0.098803936
[16]  0.054302255  0.010458550  0.027084171  0.093360275 -0.086770544
[21] -0.058311865 -0.137652494  0.045886380  0.041093334  0.026722690
[26]  0.018887859  0.041281613 -0.048607846  0.084383717 -0.023803636
[31]  0.012783679 -0.196751197  0.016266617 -0.023178488  0.047783177
[36]  0.026184905 -0.053732804  0.022043885  0.079749268  0.030108557
[41] -0.062663349  0.001897508 -0.044302547 -0.011279042 -0.028580114
[46]  0.075196005 -0.031258129  0.008933996
> 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/4yevb1377051338.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/5z1x41377051338.tab") 
> 
> try(system("convert tmp/15dwk1377051338.ps tmp/15dwk1377051338.png",intern=TRUE))
character(0)
> try(system("convert tmp/24a921377051338.ps tmp/24a921377051338.png",intern=TRUE))
character(0)
> try(system("convert tmp/3p4b51377051338.ps tmp/3p4b51377051338.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.936   0.425   2.340