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(1329,1385,1681,1591,1598,1557,1190,932,1664,1717,1567,1355,1430,1863,1868,1711,1873,2095,1379,1021,1999,2094,2026,1390,1744,2117,1823,1963,1816,1966,1309,1250,2184,2295,1870,1222,1640,2194,2179,1976,1850,2077,1658,1156,2400,2218,1802,1444,1804,1541,2206,1972,1815,1749,1492,1307,1916,2035,1855,1086,1951,1733,1868,1532,1894,1586,1247,1212,2119,1931,1649,1296,1625,1454,1562,1612,1648,1412,1219,1207,1614,1537,1497,1141,1135,1368,1203,1201,1190,1347,607,914,1606,1518,1120,910)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '1'
> 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/1nmcy1425584700.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/2udra1425584700.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/3owy61425584700.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  0.346235379  0.231331432  0.460088121  0.501369900
 [6]  0.213725965  0.340208410  0.420695363  0.245430139  0.174269222
[11]  0.374523276  0.198397794 -0.034142393  0.175194626  0.284209956
[16]  0.041559109  0.094314398  0.203994119  0.145931339  0.022844883
[21]  0.162364949  0.166990424  0.038551912  0.111829651  0.153903663
[26]  0.119388735 -0.007733566  0.121793043  0.121764940 -0.008169919
[31]  0.001640246  0.111248442 -0.097859759 -0.033441864 -0.012983023
[36] -0.026918146 -0.162268633 -0.015504316 -0.017463362 -0.111400573
[41] -0.154427437 -0.056161104 -0.156099210 -0.177432812 -0.084292871
[46] -0.086428780 -0.150376317 -0.080158792 -0.130025306
> (mypacf <- c(rpacf$acf))
 [1]  0.346235379  0.126633140  0.399870470  0.337810656 -0.056326219
 [6]  0.148345607  0.084085089 -0.063492427 -0.060396595  0.100548093
[11] -0.138062549 -0.279554067 -0.001653320  0.090794035  0.023888555
[16]  0.162494325  0.041466149  0.102032940  0.032177918  0.025105944
[21]  0.016728102 -0.032387851 -0.016205478 -0.181015208  0.044111531
[26] -0.139178590 -0.010630851  0.063009226 -0.057696214  0.005207465
[31]  0.056268552 -0.203408287  0.084825442 -0.089472510 -0.012223793
[36] -0.086757178  0.104323138  0.023007764  0.018015574  0.058913901
[41] -0.147911515 -0.072369686 -0.087647998 -0.089972727  0.014880723
[46]  0.071332369  0.072331733 -0.082857606
> 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/4n4e11425584700.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/5pnx11425584700.tab") 
> 
> try(system("convert tmp/1nmcy1425584700.ps tmp/1nmcy1425584700.png",intern=TRUE))
character(0)
> try(system("convert tmp/2udra1425584700.ps tmp/2udra1425584700.png",intern=TRUE))
character(0)
> try(system("convert tmp/3owy61425584700.ps tmp/3owy61425584700.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.299   0.282   1.588