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(11798,8378,8131,7676,7505,8168,6455,6141,6554,6888,5339,1624,9187,5047,5289,4169,3862,4253,3768,3066,4108,3890,3420,1221,5984,4064,5151,4027,3530,4819,3855,3584,4322,4154,4656,1464,7780,5060,6084,4778,4989,4903,4142,4101,4595,5034,5407,1782,8395,5291,6116,4210,4621,5299,4293,4542,3831,4360,4088,1508,6743,4159,5105,4283,4019,4206,3948,3407,3701,4159,4208,2622)
> 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/11n441413542461.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/2zr021413542461.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/3mx1z1413542461.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  0.225326322  0.389129276  0.273822620  0.312583584
 [6]  0.263476814  0.064263032  0.158099858  0.147455178  0.051647286
[11]  0.058072147 -0.189580599  0.444166131 -0.171241846 -0.032160622
[16] -0.159792074 -0.096649172 -0.109276510 -0.233917668 -0.144292294
[21] -0.113716412 -0.155270082 -0.103280943 -0.271228750  0.258054615
[26] -0.172724428 -0.035450681 -0.119425038 -0.037933331 -0.042153400
[31] -0.124078744 -0.030771684 -0.012609744 -0.011948060  0.033708437
[36] -0.106689329  0.330886262 -0.006839331  0.068177214  0.003660249
[41]  0.068084843  0.047466271 -0.027128038  0.046926684  0.042777173
[46]  0.056995495  0.054393766 -0.061532237  0.241591294
> (mypacf <- c(rpacf$acf))
 [1]  0.225326322  0.356455254  0.165428515  0.151842100  0.093625420
 [6] -0.184739679 -0.029229672  0.083800640 -0.058516819 -0.009720558
[11] -0.280753849  0.593800816 -0.394540852 -0.236354173 -0.118814915
[16] -0.065579040 -0.058772553  0.128974358  0.025954705 -0.025405889
[21] -0.030453776  0.056677845  0.168209580 -0.063201346 -0.030463908
[26] -0.093116732 -0.015433681 -0.016742425 -0.001719573 -0.043293259
[31]  0.042387921 -0.061247493  0.112975261  0.082759508 -0.022518151
[36]  0.047963488 -0.028702451 -0.114314906  0.022097525  0.025458438
[41] -0.024135038  0.027441207  0.005028265  0.053002646  0.034612437
[46] -0.049495607  0.046024115 -0.152105928
> 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/4xdyx1413542461.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/5xvnl1413542461.tab") 
> 
> try(system("convert tmp/11n441413542461.ps tmp/11n441413542461.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zr021413542461.ps tmp/2zr021413542461.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mx1z1413542461.ps tmp/3mx1z1413542461.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.165   0.222   1.400