R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(0.67,0.66,0.66,0.67,0.67,0.67,0.67,0.68,0.68,0.67,0.67,0.67,0.67,0.67,0.69,0.69,0.69,0.69,0.69,0.69,0.7,0.69,0.68,0.7,0.7,0.71,0.69,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.69,0.7,0.7,0.7,0.71,0.7,0.7,0.69,0.7,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.69,0.7,0.7,0.7,0.72,0.7,0.69,0.7,0.71,0.72,0.72,0.73,0.72,0.74,0.75)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '0.0'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '0.0'
> 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/1yjj11353091813.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/2fj4l1353091813.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/356w11353091813.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 -0.216417712 -0.109426484 -0.086641137 -0.061989338
 [6]  0.090204140  0.095443219  0.119340827 -0.215062673  0.012383807
[11]  0.021497747 -0.039934796  0.131550049 -0.079566777 -0.111577997
[16]  0.009437556 -0.059739681  0.192037200 -0.026030541 -0.123161839
[21]  0.033121130  0.085291591 -0.070385274 -0.005778278  0.104319855
[26] -0.053421691 -0.029498101 -0.044284995 -0.131402852  0.120855629
[31]  0.031107001  0.017713310 -0.076820738 -0.083678304 -0.045194308
[36]  0.012437519  0.150531522 -0.059340857  0.069529818 -0.102317036
[41] -0.141588641  0.224559736 -0.047253288 -0.035056699 -0.058279317
[46]  0.047464895  0.007251137  0.112812083 -0.031471512
> (mypacf <- c(rpacf$acf))
 [1] -0.216417712 -0.163941581 -0.161377840 -0.158756655 -0.006849289
 [6]  0.080792337  0.187583875 -0.101838619  0.007782227  0.019652948
[11] -0.070415498  0.059626165 -0.054779044 -0.129634679 -0.022383135
[16] -0.148701138  0.124581618  0.030238715 -0.128050886  0.090276567
[21]  0.144999362 -0.089189900 -0.011577214  0.046241222  0.046632315
[26] -0.007648187 -0.181816882 -0.199210622  0.034502629 -0.078587281
[31]  0.047005408 -0.022864679 -0.106092191 -0.046909510 -0.060275657
[36]  0.063189366  0.013091737  0.037338336  0.040280110 -0.124465793
[41]  0.023369527 -0.109153233 -0.110851659 -0.070430941  0.036326225
[46] -0.026809337  0.139512228 -0.050493827
> 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/4q7g11353091813.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/54pj51353091813.tab") 
> 
> try(system("convert tmp/1yjj11353091813.ps tmp/1yjj11353091813.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fj4l1353091813.ps tmp/2fj4l1353091813.png",intern=TRUE))
character(0)
> try(system("convert tmp/356w11353091813.ps tmp/356w11353091813.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  6.043   1.306   7.361