R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(3.96,3.97,3.96,3.95,3.94,3.94,3.95,3.93,3.94,3.92,3.95,3.94,3.95,3.92,3.92,3.92,3.92,3.9,3.92,3.94,3.96,3.95,3.96,3.97,3.99,4,4.05,4.08,4.09,4.12,4.14,4.15,4.15,4.15,4.15,4.2,4.22,4.22,4.22,4.23,4.3,4.29,4.32,4.31,4.35,4.34,4.35,4.38,4.39,4.38,4.34,4.33,4.33,4.33,4.33,4.32,4.35,4.35,4.35,4.36,4.38,4.41,4.43,4.42,4.43,4.43,4.42,4.46,4.44,4.41,4.41,4.46,4.5,4.58,4.61,4.65,4.55,4.63,4.69,4.72,4.71,4.74,4.77,4.78)
> 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/fisher/rcomp/tmp/1rd6f1384810059.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/fisher/rcomp/tmp/22ol61384810059.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/fisher/rcomp/tmp/3hrvb1384810059.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  0.958770495  0.917731116  0.877072891  0.839362509
 [6]  0.795929366  0.753837283  0.716128711  0.683384664  0.639202112
[11]  0.597644642  0.559376333  0.526918379  0.497778785  0.470979538
[16]  0.443115592  0.411914273  0.377081115  0.343580190  0.308700180
[21]  0.274218980  0.241172996  0.205237114  0.172105801  0.143499914
[26]  0.118430352  0.093988201  0.071189501  0.049806552  0.032549767
[31]  0.016090602 -0.000426054 -0.017560842 -0.035208967 -0.055281412
[36] -0.080412086 -0.105696218 -0.128917721 -0.151216438 -0.174741235
[41] -0.199730447 -0.216630521 -0.235583945 -0.251799569 -0.270943118
[46] -0.281882096 -0.293048771 -0.305213828 -0.317160921
> (mypacf <- c(rpacf$acf))
 [1]  0.958770495 -0.018694443 -0.016673463  0.014884060 -0.091306205
 [6] -0.007292972  0.031439705  0.035080922 -0.156688098  0.008964101
[11]  0.013125802  0.033261167  0.044334167  0.010021332 -0.045188672
[16] -0.080262931 -0.045363740 -0.008397676 -0.038549407 -0.023200481
[21] -0.012343431 -0.076720866  0.014366576  0.052032455  0.028259438
[26] -0.019639292 -0.008245810 -0.025487253  0.014079736  0.016106987
[31] -0.018048135 -0.038933487 -0.043827804 -0.046840015 -0.076525883
[36] -0.007379775  0.004091109 -0.018643201 -0.048068428 -0.049675154
[41]  0.071819969 -0.052074705  0.025401805 -0.071793505  0.034511263
[46] -0.039137548 -0.029616675  0.008614792
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4uxmw1384810059.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/fisher/rcomp/tmp/5fuz91384810059.tab") 
> 
> try(system("convert tmp/1rd6f1384810059.ps tmp/1rd6f1384810059.png",intern=TRUE))
character(0)
> try(system("convert tmp/22ol61384810059.ps tmp/22ol61384810059.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hrvb1384810059.ps tmp/3hrvb1384810059.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.810   0.405   2.199