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(7.08,7.08,7.09,7.07,7.06,6.99,6.99,6.99,6.98,6.96,6.95,6.91,6.91,6.87,6.91,6.89,6.88,6.9,6.91,6.85,6.86,6.82,6.8,6.83,6.84,6.89,7.14,7.21,7.25,7.31,7.3,7.48,7.49,7.4,7.44,7.42,7.14,7.24,7.33,7.61,7.66,7.69,7.7,7.68,7.71,7.71,7.72,7.68,7.72,7.74,7.76,7.9,7.97,7.96,7.95,7.97,7.93,7.99,7.96,7.92,7.97,7.98,8,8.04,8.17,8.29,8.26,8.3,8.32,8.28,8.27,8.32,8.31,8.34,8.32,8.36,8.33,8.35,8.34,8.37,8.31,8.33,8.34,8.25,8.27,8.31,8.25,8.3,8.3,8.35,8.78,8.9,8.9,8.9,9,9.05)
> 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. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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/10o1x1321617491.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/2kqq81321617491.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/31v0v1321617491.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  0.169154716  0.003539683  0.034554380 -0.060794810
 [6] -0.052044555 -0.007028344 -0.143644410  0.006364584 -0.041543974
[11] -0.132261962  0.063806088  0.089492603  0.152637370  0.073663672
[16] -0.094944484 -0.103820393 -0.008522559 -0.125202167 -0.089338683
[21] -0.017991133 -0.123747261 -0.034274694  0.055657809 -0.020857000
[26]  0.180040378  0.151381912  0.017934098 -0.086907465 -0.092379847
[31] -0.004419762 -0.047120428 -0.110017593  0.050025082 -0.001879611
[36] -0.084960892  0.000747275 -0.004270478  0.068520563  0.109560096
[41]  0.036418741 -0.043899386  0.006298182 -0.076135651 -0.039426592
[46] -0.033421801 -0.032594829 -0.004773149 -0.009934190
> (mypacf <- c(rpacf$acf))
 [1]  1.691547e-01 -2.581221e-02  3.946108e-02 -7.571526e-02 -2.845026e-02
 [6]  3.459463e-03 -1.444236e-01  5.853811e-02 -6.788162e-02 -1.084200e-01
[11]  9.254619e-02  5.394484e-02  1.513239e-01 -2.172316e-02 -1.068704e-01
[16] -8.119758e-02  7.211155e-05 -8.463184e-02 -6.276787e-02  1.141600e-02
[21] -1.133180e-01 -1.280998e-03  6.596622e-02 -5.901942e-02  1.308767e-01
[26]  4.164744e-02  1.432565e-02 -1.369118e-01 -4.234072e-02  6.818091e-02
[31] -9.690326e-02 -2.599313e-02  9.319053e-02 -3.634408e-02 -6.441809e-02
[36] -3.856977e-02 -4.013228e-02 -5.610268e-03  3.074940e-02  5.951097e-02
[41] -1.411888e-02  1.550540e-02 -6.902638e-02  9.588108e-03 -3.134880e-02
[46] -3.240683e-02  4.665039e-03 -9.107475e-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/4b23i1321617491.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/5htfz1321617491.tab") 
> 
> try(system("convert tmp/10o1x1321617491.ps tmp/10o1x1321617491.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kqq81321617491.ps tmp/2kqq81321617491.png",intern=TRUE))
character(0)
> try(system("convert tmp/31v0v1321617491.ps tmp/31v0v1321617491.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.038   0.196   1.231