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(389.09,391.76,390.96,391.76,392.8,393.06,393.06,393.26,393.87,394.47,394.57,394.57,394.57,399.57,406.13,407.03,409.46,409.9,409.9,410.14,410.54,410.69,410.79,410.97,410.97,413.8,423.31,423.85,426.6,426.26,426.26,426.32,427.14,427.55,428.29,428.8,428.8,434.87,435.66,440.75,440.99,441.04,441.04,441.88,441.92,442.48,442.81,442.81,442.81,447.19,446.52,448.57,448.71,448.73,449.07,449.03,448.68,450.08,449.96,449.96,449.96,452.56,455.31,456.2,456.75,457.63,457.63,457.65,458.32,459.64,460.16,459.89)
> 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/179zp1413637454.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/2ngom1413637454.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/3f20p1413637454.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  0.099498697  0.127320854 -0.125068309 -0.162582357
 [6] -0.161882535 -0.096718792 -0.175767724 -0.152510822 -0.087746812
[11]  0.015143462  0.200389872  0.463390484  0.309815784  0.013645403
[16] -0.104708234 -0.166556146 -0.104521202 -0.093901198 -0.126652794
[21] -0.108140569 -0.052725175 -0.080299713  0.304805437  0.089249941
[26]  0.222913953  0.017419134 -0.100393706 -0.111963224 -0.070902131
[31] -0.103649284 -0.053454299 -0.104895181 -0.046038260 -0.084625436
[36]  0.130079866  0.176266254 -0.001815326  0.024244774 -0.051831889
[41] -0.063807722 -0.057704761 -0.056393968 -0.016763179 -0.027370985
[46] -0.058907709 -0.017863870  0.023178017  0.140651582
> (mypacf <- c(rpacf$acf))
 [1]  0.099498697  0.118594952 -0.151647294 -0.158398728 -0.103850679
 [6] -0.053347062 -0.184210203 -0.192073136 -0.109766910 -0.040894510
[11]  0.107084009  0.388475369  0.271196095 -0.090522770 -0.117665098
[16] -0.019480475  0.061662629  0.017873165 -0.021005270  0.035941566
[21]  0.052471927 -0.148956149  0.181865894 -0.225639204 -0.178921482
[26]  0.008324141  0.036840497  0.028577277 -0.045185732 -0.079222629
[31]  0.012711455 -0.093109012 -0.027481693 -0.121131870 -0.104269581
[36]  0.145268667 -0.055150192 -0.089776358  0.005399980 -0.041119987
[41] -0.068283024 -0.031354657  0.053340058  0.037781209 -0.007427748
[46] -0.025835530  0.080412731 -0.051969526
> 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/4cdvf1413637454.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/5qw2i1413637454.tab") 
> 
> try(system("convert tmp/179zp1413637454.ps tmp/179zp1413637454.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ngom1413637454.ps tmp/2ngom1413637454.png",intern=TRUE))
character(0)
> try(system("convert tmp/3f20p1413637454.ps tmp/3f20p1413637454.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.132   0.192   1.341