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 = '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/1fmey1425584384.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/25gfe1425584384.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/33a3z1425584384.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  0.397159210  0.004864811  0.108043772  0.447086636
 [6]  0.359447464  0.284025641  0.349704564  0.299280819 -0.012852556
[11] -0.041548349  0.273430861  0.608486488  0.173720516 -0.135566500
[16] -0.096482626  0.200616013  0.162786680  0.093933881  0.131751604
[21]  0.093456889 -0.154701543 -0.192194972  0.140273259  0.397858816
[26]  0.010829500 -0.283182163 -0.165645962  0.084308110  0.008684252
[31] -0.040280838  0.029817197 -0.066926139 -0.268660460 -0.253723709
[36]  0.030525579  0.182099035 -0.133258342 -0.307467906 -0.222007271
[41] -0.078303911 -0.111998985 -0.111571663 -0.067878370 -0.152653199
[46] -0.292726973 -0.266927561 -0.032463235  0.076528843
> (mypacf <- c(rpacf$acf))
 [1]  0.397159210 -0.181499536  0.218343941  0.395481830  0.048807117
 [6]  0.294494538  0.285646309  0.002027746 -0.292653934 -0.219712529
[11] -0.036533142  0.436872250 -0.155972710 -0.032062434 -0.212548397
[16] -0.093534252 -0.005849282 -0.033032283  0.071462489  0.096836969
[21]  0.015756463 -0.089472450  0.064203073  0.046744791 -0.081000955
[26] -0.089557188  0.026948890 -0.084107409 -0.066793248 -0.036867321
[31] -0.010807956 -0.080850338  0.043385971 -0.009422057 -0.062061791
[36]  0.008321072 -0.085353469  0.146996634 -0.010782229 -0.133462405
[41] -0.034781771 -0.067097768 -0.059203514  0.077678597  0.036136176
[46]  0.044045779  0.004217513 -0.066031490
> 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/4hnl71425584384.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/5af6x1425584384.tab") 
> 
> try(system("convert tmp/1fmey1425584384.ps tmp/1fmey1425584384.png",intern=TRUE))
character(0)
> try(system("convert tmp/25gfe1425584384.ps tmp/25gfe1425584384.png",intern=TRUE))
character(0)
> try(system("convert tmp/33a3z1425584384.ps tmp/33a3z1425584384.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.169   0.245   1.423