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(55.7,59.2,59.8,61.6,65.8,64.2,67,62.8,65.5,75.2,80.9,83.2,83.7,86.4,85.9,80.4,81.8,87.5,83.7,87,99.7,101.4,101.9,115.7,123.2,136.9,146.8,149.6,146.5,157,147.9,133.6,128.7,100.8,91.8,89.3,96.7,91.6,93.3,93.3,101,100.4,86.9,83.9,80.3,87.7,92.7,95.5,92,87.4,86.8,83.7,85,81.7,90.9,101.5,113.8,120.1,122.1,132.5,140,149.4,144.3,154.4,151.4,145.5,136.8,146.6,145.1,133.6,131.4,127.5,130.1,131.1,132.3,128.6,125.1,128.7,156.1,163.2,159.8,157.4,156.2,152.5)
> 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/171wq1387020443.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/2bxjq1387020443.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/3og531387020443.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  0.938290504  0.856343025  0.764851386  0.667183359
 [6]  0.564636482  0.466507365  0.387276147  0.312185769  0.250244679
[11]  0.195570315  0.154309751  0.110647094  0.076222279  0.052404695
[16]  0.033026783 -0.001596013 -0.041342842 -0.073478879 -0.119303133
[21] -0.168396694 -0.214596898 -0.250808561 -0.285372411 -0.302322670
[26] -0.300678008 -0.274360403 -0.231710431 -0.182470330 -0.122746992
[31] -0.045031306  0.036912420  0.100200650  0.151551356  0.176332551
[36]  0.188226396  0.188896294  0.187988896  0.180567018  0.165908964
[41]  0.153836417  0.146212141  0.138275253  0.111585708  0.081943726
[46]  0.057589067  0.050859294  0.053640923  0.057294441
> (mypacf <- c(rpacf$acf))
 [1]  0.938290504 -0.201035519 -0.100622824 -0.086312815 -0.086564018
 [6] -0.013282778  0.093909795 -0.067117241  0.037139421 -0.032498744
[11]  0.035048478 -0.098874331  0.048859061  0.024378027 -0.004461298
[16] -0.185956310 -0.034348698  0.021881633 -0.140999805 -0.035968337
[21]  0.002264124 -0.009960249 -0.040015860  0.099558736  0.041929555
[26]  0.139099777  0.075881830  0.006062249  0.018094143  0.211778017
[31]  0.064958319 -0.108063016 -0.053289316 -0.113997521  0.003539801
[36]  0.002213255  0.069999251 -0.016078576 -0.045529935 -0.018873571
[41]  0.022683868 -0.069230530 -0.137865308 -0.066839923 -0.027227152
[46]  0.128170161  0.149263853 -0.043090750
> 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/4t3c11387020443.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/5maiw1387020443.tab") 
> 
> try(system("convert tmp/171wq1387020443.ps tmp/171wq1387020443.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bxjq1387020443.ps tmp/2bxjq1387020443.png",intern=TRUE))
character(0)
> try(system("convert tmp/3og531387020443.ps tmp/3og531387020443.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.522   0.735   4.218