R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1165010
+ ,1160665
+ ,1156265
+ ,1147162.5
+ ,1237238.75
+ ,1232481.25
+ ,1165010
+ ,1120157.5
+ ,1124488.75
+ ,1124488.75
+ ,1129328.75
+ ,1138005
+ ,1151507.5
+ ,1151507.5
+ ,1142831.25
+ ,1120157.5
+ ,1237238.75
+ ,1255086.25
+ ,1228136.25
+ ,1165010
+ ,1192015
+ ,1151507.5
+ ,1169781.25
+ ,1178512.5
+ ,1187615
+ ,1165010
+ ,1169781.25
+ ,1138005
+ ,1237238.75
+ ,1268588.75
+ ,1241638.75
+ ,1192015
+ ,1245983.75
+ ,1187615
+ ,1241638.75
+ ,1237238.75
+ ,1250755
+ ,1201131.25
+ ,1255086.25
+ ,1250755
+ ,1331715
+ ,1313441.25
+ ,1241638.75
+ ,1205462.5
+ ,1255086.25
+ ,1187615
+ ,1237238.75
+ ,1245983.75
+ ,1264257.5
+ ,1223805
+ ,1245983.75
+ ,1259486.25
+ ,1309110
+ ,1268588.75
+ ,1214633.75
+ ,1156265
+ ,1210288.75
+ ,1061788.75
+ ,1133660
+ ,1174112.5
+ ,1214633.75
+ ,1156265
+ ,1156265
+ ,1156265
+ ,1187615
+ ,1142831.25
+ ,1084036.25
+ ,1034838.75
+ ,1070533.75
+ ,931205
+ ,1016578.75
+ ,1066188.75
+ ,1075305
+ ,1025681.25
+ ,1030012.5
+ ,1016578.75
+ ,1061788.75
+ ,1030012.5
+ ,967381.25
+ ,922102.5
+ ,998662.5
+ ,832383.75
+ ,940362.5
+ ,989560
+ ,989560
+ ,931205
+ ,877236.25
+ ,872905
+ ,922102.5
+ ,877236.25
+ ,791931.25
+ ,733136.25
+ ,796276.25
+ ,647831.25
+ ,782760
+ ,854562.5
+ ,877236.25
+ ,827626.25
+ ,764926.25
+ ,809778.75
+ ,827626.25
+ ,814110
+ ,679126.25
+ ,616481.25
+ ,661278.75
+ ,526350
+ ,665678.75
+ ,715302.5
+ ,755755
+ ,688283.75
+ ,625157.5
+ ,661278.75
+ ,679126.25
+ ,643431.25
+ ,508502.5
+ ,449707.5
+ ,503676.25
+ ,355231.25
+ ,517178.75
+ ,616481.25)
> 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/fisher/rcomp/tmp/1hdv51377009165.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/2qwtp1377009165.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/3jy3q1377009165.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 -0.216917539 -0.052806118 -0.144745750  0.067045987
 [6] -0.127175085  0.050547264 -0.084735516  0.084992012 -0.162069442
[11] -0.039784416 -0.178023983  0.824286736 -0.222705754 -0.040322706
[16] -0.126454361  0.071269168 -0.148903442  0.078644461 -0.087457571
[21]  0.093320872 -0.122644165 -0.020611578 -0.146853171  0.675932383
[26] -0.227437000 -0.032943652 -0.105113723  0.066529789 -0.166063313
[31]  0.104597417 -0.071957279  0.087001092 -0.110977987 -0.009743632
[36] -0.106328119  0.538601063 -0.216564657 -0.033409561 -0.080533868
[41]  0.018628376 -0.174372650  0.110770746 -0.049792991  0.094974485
[46] -0.090022527 -0.015288246 -0.057292723  0.413164742
> (mypacf <- c(rpacf$acf))
 [1] -0.216917539 -0.104790046 -0.191124444 -0.021971698 -0.161874231
 [6] -0.047106445 -0.123983734 -0.013624715 -0.190298571 -0.202363289
[11] -0.356781368  0.754902761  0.022645421  0.021995121 -0.014812725
[16]  0.043260558  0.008477895  0.077156219 -0.100724062 -0.019274112
[21]  0.140129650  0.053461811  0.021172015 -0.005973974 -0.016189665
[26]  0.003903323  0.043716353 -0.046816806 -0.046616083  0.025734282
[31]  0.071140797 -0.010280710 -0.060121947 -0.048447600  0.058718685
[36] -0.025623731  0.001576123 -0.081761100  0.006192215 -0.123169698
[41] -0.043846117 -0.129003491 -0.025583632  0.015933935  0.019635028
[46] -0.090493836  0.040296831 -0.056767513
> 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/4cutv1377009165.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/5livk1377009165.tab") 
> 
> try(system("convert tmp/1hdv51377009165.ps tmp/1hdv51377009165.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qwtp1377009165.ps tmp/2qwtp1377009165.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jy3q1377009165.ps tmp/3jy3q1377009165.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.884   0.523   2.387