R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(695,638,762,635,721,854,418,367,824,687,601,676,740,691,683,594,729,731,386,331,707,715,657,653,642,643,718,654,632,731,392,344,792,852,649,629,685,617,715,715,629,916,531,357,917,828,708,858)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> 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 (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> 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/11d4h1324649514.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=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2pcnz1324649514.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')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.066467951 -0.426652701  0.108670456 -0.017820922
 [6] -0.073736534  0.075434242 -0.064241552  0.069295032  0.048331887
[11] -0.302976432  0.047269407  0.607039431  0.073671976 -0.345870091
[16] -0.049480562 -0.041500848 -0.099260413  0.022237785 -0.050929860
[21] -0.015220982  0.067437276 -0.166173422 -0.044370514  0.372705679
[26]  0.040405198 -0.328670822 -0.061150216  0.009444593 -0.073504391
[31]  0.015340194 -0.007374156 -0.017291304  0.087782970 -0.081283184
[36] -0.070133131  0.221927090  0.009793906 -0.173905584  0.041532409
[41] -0.033593344 -0.053679862  0.066106325  0.012132955  0.005757452
[46]  0.025448226 -0.002516332  0.007104719
> (mypacf <- c(rpacf$acf))
 [1]  0.066467951 -0.432983606  0.220150547 -0.320688183  0.198946355
 [6] -0.193032024  0.065693826  0.074369947 -0.100655003 -0.212824548
[11]  0.169671103  0.513396029 -0.024326484  0.049855758 -0.242502408
[16] -0.011481810 -0.188498561  0.001247264 -0.174309802 -0.161072955
[21]  0.093930977 -0.107501819  0.095903478 -0.147586873 -0.002351068
[26] -0.164834603  0.083025432  0.022209784 -0.013483788  0.012671199
[31] -0.018940930  0.030570388  0.023387487 -0.081526619 -0.015213930
[36] -0.172272504  0.017244028  0.158492382  0.044190559 -0.056657722
[41] -0.085896347 -0.005151750  0.061765567 -0.020585100 -0.176289340
[46]  0.084915832 -0.059743505
> 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/3xa0u1324649514.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/49ezs1324649514.tab") 
> 
> try(system("convert tmp/11d4h1324649514.ps tmp/11d4h1324649514.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pcnz1324649514.ps tmp/2pcnz1324649514.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.736   0.140   0.874