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(120.6,119.9,119.48,117.45,118.37,117.07,114.98,112.59,111.7,112.04,110.79,109.82,109.11,109.84,109.31,108.29,107.42,106.71,105.11,104.43,105.55,106.12,105.78,105.33,104.63,104.62,105.57,107.5,107.52,107.76,106.74,106.21,105.77,105.27,104.35,103.52,102.28,100.93,101.04,99.95,99.55,99.56,99.01,98.64,98.98,100.8,100.32,100.72,280.8,280.4,280.4,280.3,281,280.9,279.7,283.1,290.6,291.6,291.7,291.8,291.7,291.5,291.7,293.4,293.1,293.1,292.6,292.1,292.2,292,292.1,293.4,292.2,292.1,291.6,290.9,290.9,290.8,290.5,290,290.2,290.1,291,291.8)
> 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/fisher/rcomp/tmp/19ksf1384789096.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/fisher/rcomp/tmp/25pws1384789096.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/fisher/rcomp/tmp/379vs1384789096.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  0.96490783  0.92980463  0.89491972  0.85936353  0.82363032
 [7]  0.78780472  0.75218193  0.71539054  0.67663819  0.63783868  0.59879919
[13]  0.55996230  0.52121049  0.48300358  0.44495627  0.40645660  0.36809888
[19]  0.32975295  0.29156956  0.25341414  0.21530888  0.17708402  0.13860209
[25]  0.09971591  0.06124798  0.02293385 -0.01505815 -0.05269438 -0.08947330
[31] -0.12552795 -0.16139064 -0.19701116 -0.23239112 -0.26753624 -0.30286460
[37] -0.33875159 -0.34657014 -0.35419043 -0.36152627 -0.36875624 -0.37571715
[43] -0.38209081 -0.38805048 -0.39371278 -0.39963787 -0.40500204 -0.41026415
[49] -0.41550821
> (mypacf <- c(rpacf$acf))
 [1]  0.96490783 -0.01801945 -0.01502314 -0.02815173 -0.02168204 -0.02099944
 [7] -0.01701966 -0.03728326 -0.04996362 -0.02407602 -0.02719134 -0.02099353
[13] -0.02358085 -0.01754179 -0.02340685 -0.03204080 -0.02467680 -0.02780292
[19] -0.02624387 -0.02931396 -0.02997958 -0.03373781 -0.03623815 -0.03963238
[25] -0.02933984 -0.03399779 -0.03268563 -0.03339147 -0.02710871 -0.02942094
[31] -0.03780331 -0.03902313 -0.04119803 -0.04282965 -0.05117536 -0.05977534
[37]  0.36685178 -0.02227198 -0.01684011 -0.03172671 -0.02270208 -0.01663747
[43] -0.01518106 -0.03483484 -0.05716751 -0.02046533 -0.03157347 -0.02707467
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4djir1384789096.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/fisher/rcomp/tmp/5o5fe1384789096.tab") 
> 
> try(system("convert tmp/19ksf1384789096.ps tmp/19ksf1384789096.png",intern=TRUE))
character(0)
> try(system("convert tmp/25pws1384789096.ps tmp/25pws1384789096.png",intern=TRUE))
character(0)
> try(system("convert tmp/379vs1384789096.ps tmp/379vs1384789096.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.658   0.413   2.051