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 = '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/1ht961413637328.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/2nwil1413637328.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/3jibz1413637328.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  0.96235106  0.92479370  0.88418788  0.84445400  0.80554399
 [7]  0.76607798  0.72534096  0.68477138  0.64437750  0.60404875  0.56424702
[13]  0.52364181  0.47839463  0.43474603  0.39618466  0.35888339  0.32336601
[19]  0.28743056  0.25085768  0.21380941  0.17642647  0.13974792  0.10155996
[25]  0.06391667  0.02424632 -0.01529129 -0.04598641 -0.07622145 -0.10402277
[31] -0.13218880 -0.16089857 -0.19038088 -0.21936826 -0.24444571 -0.26863981
[37] -0.28891963 -0.31123725 -0.32761956 -0.34349715 -0.35409843 -0.36403410
[43] -0.37420241 -0.38474024 -0.39532015 -0.40405702 -0.41207518 -0.41207859
[49] -0.41023962
> (mypacf <- c(rpacf$acf))
 [1]  0.962351061 -0.017946059 -0.060786378 -0.009865401 -0.008683837
 [6] -0.029989714 -0.040494156 -0.020507884 -0.020304786 -0.024469678
[11] -0.018511019 -0.036027352 -0.090362351 -0.008323154  0.044577094
[16] -0.013492712 -0.010129016 -0.030529754 -0.034830780 -0.036899399
[21] -0.036846284 -0.022379320 -0.054358093 -0.026385642 -0.056442453
[26] -0.041591306  0.076656694 -0.025829702 -0.007402825 -0.032494156
[31] -0.037276287 -0.046855984 -0.035204908  0.015042727 -0.024432352
[36]  0.013176752 -0.059631640  0.040696988 -0.041706612  0.035642739
[41] -0.009342008 -0.033517955 -0.026230173 -0.033063475 -0.009038078
[46] -0.035626096  0.079261671  0.003459966
> 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/4sno41413637328.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/5okp91413637328.tab") 
> 
> try(system("convert tmp/1ht961413637328.ps tmp/1ht961413637328.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nwil1413637328.ps tmp/2nwil1413637328.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jibz1413637328.ps tmp/3jibz1413637328.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.145   0.188   1.341