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(740,730,740,820,820,850,870,930,890,790,840,880,730,730,770,880,820,900,940,1080,920,710,880,910,680,740,740,810,800,900,920,1030,910,720,930,900,680,770,770,810,810,910,820,980,830,760,930,910,640,780,690,820,800,910,850,980,830,820,1010,930,630,760,670,850,780,900,840,1050,810,860,1020,820,670,780,690,800,810,910,870,1010,810,960,990,780,700,810,760,810,840,900,920,1050,860,870,880,860,650,830,730,810,840,940,870,940,770,870,860,760)
> 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/1rg7w1408315812.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/2req01408315812.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/3y6nh1408315812.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  0.216334668  0.061788822  0.036824195 -0.089051757
 [6] -0.476578149 -0.335149886 -0.463332157 -0.070998076  0.034076956
[11]  0.039197080  0.282298223  0.820738062  0.109975933  0.059188068
[16]  0.041478461 -0.112273823 -0.438428605 -0.294878529 -0.400352504
[21] -0.048196377  0.006793887  0.020358902  0.274295036  0.670940521
[26]  0.032236260  0.084379867  0.072030332 -0.084613793 -0.346182239
[31] -0.254373716 -0.350777740 -0.032303279 -0.038472821 -0.006579633
[36]  0.257276496  0.516962425 -0.012333845  0.138804489  0.086448328
[41] -0.062164161 -0.267009405 -0.209317454 -0.278440082 -0.037872123
[46] -0.078543251 -0.022496787  0.248417618  0.388405608
> (mypacf <- c(rpacf$acf))
 [1]  0.216334668  0.015724029  0.021265935 -0.107264421 -0.464560043
 [6] -0.209162791 -0.493512959  0.030062146 -0.033511906 -0.238643948
[11]  0.069435761  0.654403944 -0.243758208 -0.068470154 -0.016447661
[16] -0.005554849  0.053473162  0.029208782  0.032092852 -0.090721304
[21] -0.091709770 -0.057139870 -0.162995980  0.059278297 -0.062767882
[26]  0.011205719  0.040351603  0.033488605  0.107826350 -0.126147540
[31] -0.033290411  0.009305629 -0.079427514  0.059721274 -0.038943911
[36] -0.084746491 -0.041004344  0.012136062 -0.058511779 -0.076500549
[41]  0.036552565  0.006415624  0.065105566 -0.052483716 -0.015873054
[46] -0.014132253  0.016394369  0.016979201
> 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/4vjtm1408315812.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/56isj1408315812.tab") 
> 
> try(system("convert tmp/1rg7w1408315812.ps tmp/1rg7w1408315812.png",intern=TRUE))
character(0)
> try(system("convert tmp/2req01408315812.ps tmp/2req01408315812.png",intern=TRUE))
character(0)
> try(system("convert tmp/3y6nh1408315812.ps tmp/3y6nh1408315812.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.192   0.179   1.382