R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(840,880,930,920,940,880,980,860,900,930,870,1000,870,860,930,980,1010,860,1140,880,800,900,900,1000,890,890,870,1000,1050,790,1160,830,730,950,980,910,840,860,880,1030,1060,770,1140,890,740,860,1050,840,810,830,920,1070,1040,740,1250,850,790,810,1080,760,840,820,900,1010,1080,780,1150,820,790,820,1130,800,890,810,950,1090,1090,850,1200,790,800,850,1230,800,930,700,1030,1040,1000,830,1190,720,810,870,1190,800,970,690,1010,1030,950,830,1150,750,840,880,1210,830)
> 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/1n3s51344780049.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/2vmoc1344780049.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/3fd0n1344780049.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 -0.30308907 -0.08147904 -0.14956224  0.24194876 -0.27941544
 [7]  0.19421824 -0.21697723  0.19393352 -0.15760911 -0.06417299 -0.24305197
[13]  0.85182757 -0.28899501 -0.07594579 -0.13958674  0.22067783 -0.25963929
[19]  0.14107179 -0.16854426  0.15316919 -0.11705696 -0.08371140 -0.15332761
[25]  0.68178590 -0.25612825 -0.05499087 -0.10447646  0.19412383 -0.22237303
[31]  0.10714796 -0.11414824  0.11899699 -0.08435307 -0.10523681 -0.07263841
[37]  0.51888807 -0.21245106 -0.05058345 -0.08260947  0.16549529 -0.18274516
[43]  0.08590961 -0.08402786  0.07930353 -0.05480274 -0.11122859 -0.01445569
[49]  0.37581955
> (mypacf <- c(rpacf$acf))
 [1] -0.303089069 -0.190876508 -0.270640512  0.092112731 -0.268430077
 [6]  0.058511443 -0.231763417  0.014718822 -0.110567232 -0.337895059
[11] -0.450367095  0.718507523  0.135730824  0.079158467 -0.004796446
[16] -0.208919612  0.116069729 -0.207708694 -0.096619962 -0.081185891
[21]  0.042743245 -0.018663708  0.066687120 -0.152781595 -0.066883679
[26]  0.075502542 -0.015188129  0.102715251 -0.001001569  0.056224748
[31]  0.123662689  0.015402110 -0.041849128 -0.066059603 -0.026558957
[36] -0.072841468  0.004795235 -0.093028926 -0.082241339  0.007324201
[41] -0.023276905  0.066225502 -0.033918835 -0.082785073  0.036793270
[46]  0.046109583  0.016742383 -0.038068017
> 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/4ehrd1344780049.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/5gctl1344780049.tab") 
> 
> try(system("convert tmp/1n3s51344780049.ps tmp/1n3s51344780049.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vmoc1344780049.ps tmp/2vmoc1344780049.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fd0n1344780049.ps tmp/3fd0n1344780049.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.385   0.281   1.656