R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(26.663
+ ,23.598
+ ,26.931
+ ,24.740
+ ,25.806
+ ,24.364
+ ,24.477
+ ,23.901
+ ,23.175
+ ,23.227
+ ,21.672
+ ,21.870
+ ,21.439
+ ,21.089
+ ,23.709
+ ,21.669
+ ,21.752
+ ,20.761
+ ,23.479
+ ,23.824
+ ,23.105
+ ,23.110
+ ,21.759
+ ,22.073
+ ,21.937
+ ,20.035
+ ,23.590
+ ,21.672
+ ,22.222
+ ,22.123
+ ,23.950
+ ,23.504
+ ,22.238
+ ,23.142
+ ,21.059
+ ,21.573
+ ,21.548
+ ,20.000
+ ,22.424
+ ,20.615
+ ,21.761
+ ,22.874
+ ,24.104
+ ,23.748
+ ,23.262
+ ,22.907
+ ,21.519
+ ,22.025
+ ,22.604
+ ,20.894
+ ,24.677
+ ,23.673
+ ,25.320
+ ,23.583
+ ,24.671
+ ,24.454
+ ,24.122
+ ,24.252
+ ,22.084
+ ,22.991
+ ,23.287
+ ,23.049
+ ,25.076
+ ,24.037
+ ,24.430
+ ,24.667
+ ,26.451
+ ,25.618
+ ,25.014
+ ,25.110
+ ,22.964
+ ,23.981
+ ,23.798
+ ,22.270
+ ,24.775
+ ,22.646
+ ,23.988
+ ,24.737
+ ,26.276
+ ,25.816
+ ,25.210
+ ,25.199
+ ,23.162
+ ,24.707
+ ,24.364
+ ,22.644
+ ,25.565
+ ,24.062
+ ,25.431
+ ,24.635
+ ,27.009
+ ,26.606
+ ,26.268
+ ,26.462
+ ,25.246
+ ,25.180
+ ,24.657
+ ,23.304
+ ,26.982
+ ,26.199
+ ,27.210
+ ,26.122
+ ,26.706
+ ,26.878
+ ,26.152
+ ,26.379
+ ,24.712
+ ,25.688
+ ,24.990
+ ,24.239
+ ,26.721
+ ,23.475
+ ,24.767
+ ,26.219
+ ,28.361
+ ,28.599
+ ,27.914
+ ,27.784
+ ,25.693
+ ,26.881
+ ,26.217
+ ,24.218
+ ,27.914
+ ,26.975
+ ,28.527
+ ,27.139
+ ,28.982
+ ,28.169
+ ,28.056
+ ,29.136
+ ,26.291
+ ,26.987
+ ,26.589
+ ,24.848
+ ,27.543
+ ,26.896
+ ,28.878
+ ,27.390
+ ,28.065
+ ,28.141
+ ,29.048
+ ,28.484
+ ,26.634
+ ,27.735
+ ,27.132
+ ,24.924
+ ,28.963
+ ,26.589
+ ,27.931
+ ,28.009
+ ,29.229
+ ,28.759
+ ,28.405
+ ,27.945
+ ,25.912
+ ,26.619
+ ,26.076
+ ,25.286
+ ,27.660
+ ,25.951
+ ,26.398
+ ,25.565
+ ,28.865
+ ,30.000
+ ,29.261
+ ,29.012
+ ,26.992
+ ,27.897)
> 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: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/rcomp/tmp/13kky1272714940.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/2dt1j1272714940.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000 -0.528222798  0.234117005 -0.050322439 -0.164367496
 [6]  0.176608613 -0.271276510  0.186230441 -0.224158296  0.031848714
[11]  0.237545724 -0.454152650  0.730990114 -0.490633815  0.258283027
[16] -0.002645152 -0.132246751  0.161962882 -0.306903692  0.163194387
[21] -0.185464095  0.020873495  0.240683080 -0.425493243  0.681873325
[26] -0.471597619  0.257259681  0.002458717 -0.143534139  0.148264784
[31] -0.255877796  0.160336729 -0.199862729  0.059640045  0.162157901
[36] -0.405991965  0.656485119 -0.398891945  0.225297145 -0.024660543
[41] -0.134190196  0.121373225 -0.213187652  0.150306687 -0.185183898
[46]  0.028382727  0.147881509 -0.357062372  0.601537217
> (mypacf <- c(rpacf$acf))
 [1] -0.528222798 -0.062279505  0.067041158 -0.211492670 -0.020413776
 [6] -0.206531423 -0.075455618 -0.239057892 -0.273923157  0.151271121
[11] -0.414257594  0.453293296 -0.003783267 -0.008879299  0.208331815
[16]  0.065158956  0.060041367 -0.041328108 -0.181905472  0.026464051
[21] -0.140942451 -0.006686570 -0.065105187  0.187707037  0.036528674
[26] -0.029587068  0.105290927  0.023853720 -0.055482394  0.109252854
[31] -0.031855058 -0.043149404  0.100633547 -0.126694752 -0.103617015
[36]  0.113719003  0.098296552  0.002848922 -0.066485419 -0.013551858
[41] -0.039191867 -0.010414282 -0.012137833  0.027005211 -0.055128303
[46] -0.114003359 -0.063791054  0.050020442
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/3htip1272714940.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/www/rcomp/tmp/4kcgd1272714940.tab") 
> 
> try(system("convert tmp/13kky1272714940.ps tmp/13kky1272714940.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dt1j1272714940.ps tmp/2dt1j1272714940.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.670   0.520   1.074