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(1.38,1.96,1.36,1.24,1.35,1.23,1.09,1.08,1.33,1.35,1.38,1.5,1.47,2.09,1.52,1.29,1.52,1.27,1.35,1.29,1.41,1.39,1.45,1.53,1.45,2.11,1.53,1.38,1.54,1.35,1.29,1.33,1.47,1.47,1.54,1.59,1.5,2,1.51,1.4,1.62,1.44,1.29,1.28,1.4,1.39,1.46,1.49,1.45,2.05,1.59,1.42,1.73,1.39,1.23,1.37,1.51,1.47,1.5,1.54,1.54,2.15,1.62,1.4,1.65,1.49,1.45,1.45,1.51,1.48,1.56,1.57,1.57,2.28,1.7,1.56,1.8,1.56,1.51,1.46,1.51,1.55,1.57,1.64)
> 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/18zda1384775046.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/2w6ao1384775046.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/36ush1384775046.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 -0.398184151 -0.190290297  0.296543281 -0.145586613
 [6]  0.009086533 -0.132789966  0.002113245 -0.120769741  0.248633657
[11] -0.148129650 -0.333495554  0.811003314 -0.328931622 -0.157858236
[16]  0.268638470 -0.133799305  0.023923655 -0.099112186 -0.024973032
[21] -0.100632899  0.215539668 -0.126484705 -0.282030095  0.669062719
[26] -0.269608196 -0.124057969  0.229714527 -0.101855772 -0.008537857
[31] -0.085953433  0.001553153 -0.066233967  0.137657917 -0.088763654
[36] -0.228181514  0.525875596 -0.207103764 -0.104099897  0.195264683
[41] -0.079235187  0.001523707 -0.070775170  0.006354072 -0.056836260
[46]  0.093023671 -0.077775849 -0.173549829  0.426952883
> (mypacf <- c(rpacf$acf))
 [1] -0.398184151 -0.414571479  0.034850093 -0.063387871  0.041578065
 [6] -0.267878315 -0.221930331 -0.497602901  0.016309617 -0.226831022
[11] -0.709802458  0.191973108 -0.043835233  0.047290094 -0.144877494
[16] -0.098270213 -0.116013409  0.031544360 -0.054040410 -0.052607733
[21] -0.079209871 -0.074432686 -0.088302746 -0.041212194 -0.037412112
[26]  0.016407079 -0.029391107  0.087176981 -0.089724235 -0.144028913
[31] -0.073041073  0.135896539 -0.018002440  0.021451669 -0.080100488
[36] -0.096307094 -0.066523909 -0.048559168 -0.087195846 -0.132861900
[41] -0.050755643 -0.013609864 -0.006743256 -0.101204707 -0.069858117
[46] -0.135434087 -0.025157894  0.009705966
> 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/4p96t1384775046.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/5vz9c1384775046.tab") 
> 
> try(system("convert tmp/18zda1384775046.ps tmp/18zda1384775046.png",intern=TRUE))
character(0)
> try(system("convert tmp/2w6ao1384775046.ps tmp/2w6ao1384775046.png",intern=TRUE))
character(0)
> try(system("convert tmp/36ush1384775046.ps tmp/36ush1384775046.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.664   0.522   3.155