R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(2.32,1.93,0.62,0.6,-0.37,-1.1,-1.68,-0.77,-1.2,-0.97,-0.12,0.26,0.62,0.7,1.65,1.79,2.28,2.46,2.57,2.32,2.91,3.01,2.87,3.11,3.22,3.38,3.52,3.41,3.35,3.68,3.75,3.6,3.56,3.57,3.85,3.48,3.65,3.66,3.36,3.19,2.81,2.25,2.32,2.85,2.75,2.78,2.26,2.23,1.46,1.19,1.11,1,1.18,1.59,1.51,1.01,0.9,0.63,0.81,0.97,1.14,0.97,0.89,0.62,0.36,0.27,0.34,0.02,-0.12,0.09,-0.11,-0.38,-0.65,-0.4,-0.4,0.29,0.56,0.63,0.46,0.91,1.06,1.28,1.52,1.5)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/1mlrv1484012758.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/234qw1484012758.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/3lhmb1484012758.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  0.211984475  0.250484271  0.162181104  0.192211643
 [6] -0.142308955  0.049132704  0.121759427 -0.128749401  0.003886657
[11] -0.083273044 -0.052857258 -0.345225664  0.041165569 -0.064033499
[16] -0.038925952  0.041046145  0.045390300 -0.128843671 -0.059800957
[21] -0.038129489 -0.143615793  0.056134612  0.032968620 -0.083519713
[26] -0.139071358 -0.034837897 -0.071415110 -0.168572782 -0.003475380
[31] -0.044461583 -0.097057972 -0.068272462  0.053026644 -0.159784944
[36] -0.075098561  0.075097257 -0.017578779 -0.061705911 -0.027979958
[41]  0.016092281 -0.165183999  0.043942928  0.050225089  0.089598262
[46]  0.019245785  0.126642497 -0.019938065 -0.062631349
> (mypacf <- c(rpacf$acf))
 [1]  0.21198448  0.21521820  0.08221911  0.11074664 -0.26651164  0.04385705
 [7]  0.18806594 -0.20630354  0.07213747 -0.14742366 -0.03369074 -0.22139336
[13]  0.12801497  0.09699487 -0.02584671  0.12240453 -0.15024149 -0.14328997
[19]  0.10421012 -0.18090266  0.03865280  0.15304702 -0.08097754 -0.19491909
[25] -0.07343908 -0.01357425  0.10473585 -0.05605606 -0.02535163 -0.17131627
[31] -0.04638496 -0.02275624  0.03316018  0.01635923 -0.05319962 -0.03177141
[37] -0.07218376 -0.13935298 -0.04100607  0.01633204 -0.06142356  0.07794500
[43]  0.00480308 -0.01516306 -0.02557200 -0.07486748 -0.03500546 -0.04875110
> 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/49eni1484012758.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/5txlq1484012758.tab") 
> 
> try(system("convert tmp/1mlrv1484012758.ps tmp/1mlrv1484012758.png",intern=TRUE))
character(0)
> try(system("convert tmp/234qw1484012758.ps tmp/234qw1484012758.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lhmb1484012758.ps tmp/3lhmb1484012758.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.379   0.095   1.526