R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1516,1289,1428,1335,1402,1475,1582,1317,1450,1497,1556,981,1807,1573,1756,1708,1737,1679,1872,1598,1747,1882,1369,865,1432,1172,1268,1120,1235,1272,1360,1069,1434,1552,1584,1070,1676,1690,1643,1446,1566,1352,1805,1613,1824,1866,1774,1505,1972,1856,2037,1888,2167,2191,2036,2103,2131,2039,1983,1629,2032,2216,2141,2073,2145,2429,2157,1994,2116,2287,2162,1699)
> 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/1oidj1394805451.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/28za21394805451.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/3qhi51394805451.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  0.713465627  0.672358153  0.632281932  0.672415431
 [6]  0.510456661  0.498438555  0.390444725  0.460657783  0.322558596
[11]  0.276967678  0.214604391  0.363443735  0.202106310  0.173883346
[16]  0.161730007  0.226129173  0.097570578  0.119461024  0.055019107
[21]  0.079759376 -0.006343004 -0.019264233 -0.076767821  0.020880112
[26] -0.124323654 -0.154312543 -0.161412663 -0.117313733 -0.215930985
[31] -0.194928740 -0.201402371 -0.153769431 -0.221625290 -0.224999786
[36] -0.244861583 -0.168886191 -0.243061005 -0.264525712 -0.268737595
[41] -0.213487487 -0.260469994 -0.265495502 -0.226876105 -0.181721276
[46] -0.187971430 -0.168556048 -0.159519067 -0.090577043
> (mypacf <- c(rpacf$acf))
 [1]  7.134656e-01  3.326599e-01  1.713434e-01  2.745234e-01 -2.261376e-01
 [6]  1.165035e-02 -1.818457e-01  2.065603e-01 -1.378189e-01 -8.621028e-02
[11] -2.386059e-05  3.401953e-01 -1.830115e-01 -8.386153e-02  7.458904e-02
[16] -2.402818e-02 -9.580928e-02  2.476199e-02 -5.221229e-03 -1.903406e-01
[21]  8.176164e-03  4.551452e-02  5.124711e-03  2.525252e-02 -1.614860e-01
[26] -4.607453e-02 -8.668588e-03 -8.978978e-03  2.410872e-02 -4.232388e-02
[31]  6.592778e-02  3.010335e-02 -3.080925e-02 -9.444184e-02 -1.632603e-02
[36] -4.879835e-02 -2.597958e-03 -5.449758e-03 -6.840144e-02 -8.956740e-04
[41]  9.966788e-02 -4.033931e-02  1.212840e-01 -1.147163e-02  5.132105e-02
[46] -8.594066e-03 -3.094714e-02 -5.112715e-03
> 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/4rcnk1394805451.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/5d0ei1394805451.tab") 
> 
> try(system("convert tmp/1oidj1394805451.ps tmp/1oidj1394805451.png",intern=TRUE))
character(0)
> try(system("convert tmp/28za21394805451.ps tmp/28za21394805451.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qhi51394805451.ps tmp/3qhi51394805451.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.242   0.475   2.769