R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(500,510,590,490,540,530,550,510,390,480,530,690,570,460,540,510,520,520,580,480,410,530,540,670,570,400,510,570,470,640,650,500,340,450,600,680,630,480,400,520,470,610,670,500,290,470,660,650,570,500,400,500,340,530,680,480,340,460,630,650,550,470,240,430,390,570,700,620,280,480,560,560,560,550,140,380,390,500,750,680,280,360,590,580,490,610,170,320,440,510,770,660,300,350,580,620,490,640,150,290,370,560,780,690,310,280,590,590)
> 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/14muz1344860026.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/25u3q1344860026.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/350qr1344860026.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 -0.100950540 -0.333800142 -0.176683827 -0.152172068
 [6] -0.006903439  0.478361498  0.088067931 -0.192733855 -0.143800411
[11] -0.248883857 -0.142151518  0.772071965  0.050764816 -0.337144977
[16] -0.151491196 -0.071977338 -0.107185866  0.388666535  0.162983703
[21] -0.134641843 -0.190395023 -0.160667771 -0.154987462  0.580073482
[26]  0.153355409 -0.305075026 -0.153302476 -0.021017510 -0.135063868
[31]  0.279174389  0.197314529 -0.062322065 -0.202234006 -0.114501012
[36] -0.132696394  0.378386108  0.203722903 -0.216617171 -0.153536214
[41] -0.002103484 -0.120653124  0.141007104  0.232881734 -0.002173338
[46] -0.187997201 -0.099479130 -0.098608344  0.228403708
> (mypacf <- c(rpacf$acf))
 [1] -0.100950540 -0.347532865 -0.295515662 -0.445206892 -0.535972428
 [6] -0.081310836 -0.109928102 -0.034402495  0.056937523 -0.229420586
[11] -0.655268794  0.219027078 -0.008138120 -0.091256896  0.041147343
[16]  0.184594250  0.075079069 -0.001822360 -0.030718449  0.171435292
[21] -0.089375696 -0.056330400 -0.005178712  0.002655491 -0.004509798
[26] -0.033868045  0.037206568  0.038490973  0.018022650  0.021190066
[31] -0.056217897 -0.001712171  0.031613053  0.004284450  0.089622704
[36] -0.047879635  0.003689565  0.025300335 -0.005519459 -0.034051219
[41]  0.048864727 -0.110494253  0.006650962 -0.086815022 -0.015876948
[46] -0.017994136 -0.012931568  0.015157462
> 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/4c4bz1344860026.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/5ipor1344860026.tab") 
> 
> try(system("convert tmp/14muz1344860026.ps tmp/14muz1344860026.png",intern=TRUE))
character(0)
> try(system("convert tmp/25u3q1344860026.ps tmp/25u3q1344860026.png",intern=TRUE))
character(0)
> try(system("convert tmp/350qr1344860026.ps tmp/350qr1344860026.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.213   0.229   1.449