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(6195800,6172725,6149325,6100900,6579950,6554600,6195800,5957250,5980325,5980325,6006000,6052150,6123975,6123975,6077825,5957250,6579950,6674850,6531525,6195800,6339450,6123975,6221150,6267625,6316050,6195800,6221150,6052150,6579950,6746675,6603350,6339450,6626425,6316050,6603350,6579950,6651775,6387875,6674850,6651775,7082400,6985225,6603350,6410950,6674850,6316050,6579950,6626425,6723600,6508450,6626425,6698250,6962150,6746675,6459700,6149325,6436625,5646875,6029075,6244225,6459700,6149325,6149325,6149325,6316050,6077825,5765175,5503550,5693350,4952350,5406375,5670275,5718700,5454800,5477875,5406375,5646875,5477875,5144750,4903925,5311150,4426825,5001100,5262725,5262725,4952350,4665375,4642300,4903925,4665375,4211675,3899025,4234750,3445325,4162925,4544800,4665375,4401475,4068025,4306575,4401475,4329650,3611725,3278600,3516825,2799225,3540225,3804125,4019275,3660475,3324750,3516825,3611725,3421925,2704325,2391675,2678650,1889225,2750475,3278600)
> 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/1jzfs1439732787.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/29l2c1439732787.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/3vy981439732787.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  0.94790270  0.90526650  0.85572917  0.82620574  0.78568019
 [7]  0.75796764  0.73618879  0.72365381  0.70318234  0.69210227  0.68757109
[13]  0.70013293  0.64795997  0.60883582  0.56351155  0.53636291  0.49797273
[19]  0.47383529  0.45269086  0.44000952  0.41829281  0.40339409  0.39332445
[25]  0.39689828  0.34807438  0.31176278  0.26871560  0.24335965  0.20637754
[31]  0.18441923  0.16033689  0.14527907  0.11903014  0.10227925  0.08818946
[37]  0.08556447  0.04215289  0.01252690 -0.02312118 -0.04234608 -0.07005548
[43] -0.08184472 -0.09661699 -0.10509792 -0.12495868 -0.13603322 -0.14763354
[49] -0.15225762
> (mypacf <- c(rpacf$acf))
 [1]  0.947902704  0.066485325 -0.082604086  0.161755865 -0.095006059
 [6]  0.075233458  0.103347820  0.049089316 -0.040338340  0.088259354
[11]  0.102412095  0.170862837 -0.617564204  0.140117179  0.079109014
[16] -0.101788354  0.062871591  0.038416397 -0.041004810  0.026510362
[21] -0.026506963  0.084726623 -0.085814386 -0.059736140 -0.132116511
[26]  0.009564056  0.006385721 -0.014107807 -0.004642954  0.005718883
[31] -0.091585886  0.033591062 -0.043549144  0.058511435 -0.071713151
[36] -0.075129215  0.014526850  0.007308771 -0.021754896  0.017297289
[41]  0.014217720  0.003879167 -0.029020003 -0.021908450  0.016656330
[46] -0.028062043 -0.067435236 -0.046561609
> 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/42uba1439732787.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/5qop71439732787.tab") 
> 
> try(system("convert tmp/1jzfs1439732787.ps tmp/1jzfs1439732787.png",intern=TRUE))
character(0)
> try(system("convert tmp/29l2c1439732787.ps tmp/29l2c1439732787.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vy981439732787.ps tmp/3vy981439732787.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.242   0.172   1.420