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(193590,193745,193885,194040,194190,194345,194495,194650,194805,194955,195110,195260,195415,195570,195710,195865,196015,196170,196320,196475,196630,196780,196935,197085,197240,197395,197540,197695,197845,198000,198150,198305,198460,198610,198765,198915,199070,199225,199365,199520,199670,199825,199975,200130,200285,200435,200590,200740,200895,201050,201190,201345,201495,201650,201800,201955,202110,202260,202415,202565,202720,202875,203015,203170,203320,203475,203625,203780,203935,204085,204240,204390,204545,204700,204845,205000,205150,205305,205455,205610,205765,205915,206070,206220,206375,206530,206670,206825,206975,207130,207280,207435,207590,207740,207895,208045,208200,208355,208495,208650,208800,208955,209105,209260,209415,209565,209720,209870)
> 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/1mg5x1439766354.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/2ch481439766354.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/3fn0q1439766354.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 -0.478102446  0.136445212 -0.026310443 -0.105991564
 [6]  0.207960856 -0.445348629  0.242439194 -0.141848552  0.013848174
[11]  0.102257116 -0.420488187  0.848821375 -0.421594735  0.123724144
[16] -0.025185755 -0.091021120  0.181394033 -0.388840918  0.215872371
[21] -0.126878108  0.014972862  0.089536048 -0.363980476  0.725334262
[26] -0.365087024  0.103109702 -0.018108686 -0.083944051  0.160779590
[31] -0.340226582  0.181412173 -0.105955283  0.008204176  0.074873987
[36] -0.323259515  0.669134934 -0.324366063  0.096341015 -0.024877373
[41] -0.063021226  0.126319392 -0.291612246  0.160797730 -0.098878214
[46]  0.015281245  0.062152919 -0.266751804  0.559493576
> (mypacf <- c(rpacf$acf))
 [1] -0.478102446 -0.119438139 -0.013660724 -0.143833975  0.121779533
 [6] -0.387410348 -0.197343863 -0.183073667 -0.186619847 -0.084233467
[11] -0.630089071  0.561206632  0.230166318 -0.088988668  0.011652924
[16] -0.051165772 -0.093635070  0.138947294 -0.107722519 -0.006758931
[21] -0.041125960 -0.085216417  0.019670996  0.021235037 -0.034295854
[26] -0.010907016 -0.061326266 -0.043368487 -0.020172612 -0.039359699
[31] -0.089421650 -0.058871891 -0.085051594 -0.110561941 -0.127503216
[36]  0.112444773  0.040369229  0.012390010 -0.048765963 -0.023199895
[41] -0.057521232  0.036033271  0.023857538 -0.016439332 -0.017824167
[46]  0.024497414  0.107629098 -0.108015528
> 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/4cedr1439766354.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/5ki7e1439766354.tab") 
> 
> try(system("convert tmp/1mg5x1439766354.ps tmp/1mg5x1439766354.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ch481439766354.ps tmp/2ch481439766354.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fn0q1439766354.ps tmp/3fn0q1439766354.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.239   0.182   1.429