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(413491
+ ,399153
+ ,385939
+ ,373917
+ ,364635
+ ,364696
+ ,418358
+ ,428212
+ ,423730
+ ,420677
+ ,417428
+ ,423245
+ ,423113
+ ,418873
+ ,405733
+ ,397812
+ ,389918
+ ,391116
+ ,443814
+ ,460373
+ ,455422
+ ,456288
+ ,452233
+ ,459256
+ ,461146
+ ,451391
+ ,443101
+ ,438810
+ ,430457
+ ,435721
+ ,488280
+ ,505814
+ ,502338
+ ,500910
+ ,501434
+ ,515476
+ ,520862
+ ,519517
+ ,511805
+ ,508607
+ ,505327
+ ,511435
+ ,570158
+ ,591665
+ ,593572
+ ,586346
+ ,586063
+ ,591504
+ ,594033
+ ,585597
+ ,572450
+ ,562917
+ ,554675
+ ,553997
+ ,601310
+ ,622255
+ ,616735
+ ,606480
+ ,595079
+ ,598588
+ ,599917
+ ,591573
+ ,575489
+ ,567223
+ ,555338
+ ,555252
+ ,608249
+ ,630859
+ ,628632
+ ,624435
+ ,609670
+ ,615830
+ ,621170
+ ,604212
+ ,584348
+ ,573717
+ ,555234
+ ,544897
+ ,598866
+ ,620081
+ ,607699
+ ,589960
+ ,578665
+ ,580166
+ ,579457
+ ,571560
+ ,560460
+ ,551397
+ ,536763
+ ,540562
+ ,588184
+ ,607049
+ ,598968
+ ,577644
+ ,562640
+ ,565867
+ ,561274
+ ,554144
+ ,539900
+ ,526271
+ ,511841
+ ,505282
+ ,554083
+ ,584225
+ ,568858
+ ,539516
+ ,521612
+ ,525562
+ ,526519
+ ,515713
+ ,503454
+ ,489301
+ ,479020
+ ,475102
+ ,523682
+ ,551528
+ ,531626
+ ,511037
+ ,492417
+ ,492188
+ ,492865
+ ,480961
+ ,461935
+ ,456608
+ ,441977
+ ,439148
+ ,488180
+ ,520564
+ ,501492
+ ,485025
+ ,464196
+ ,460170
+ ,467037
+ ,460070
+ ,447988
+ ,442867
+ ,436087
+ ,431328
+ ,484015
+ ,509673
+ ,512927
+ ,502831
+ ,470984
+ ,471067
+ ,476049
+ ,474605
+ ,470439
+ ,461251
+ ,454724
+ ,455626
+ ,516847
+ ,525192
+ ,522975
+ ,518585
+ ,509239
+ ,512238
+ ,519164
+ ,517009
+ ,509933
+ ,509127
+ ,500857
+ ,506971
+ ,569323
+ ,579714
+ ,577992
+ ,565464
+ ,547344
+ ,554788
+ ,562325
+ ,560854
+ ,555332
+ ,543599
+ ,536662
+ ,542722
+ ,593530
+ ,610763
+ ,612613
+ ,611324
+ ,594167
+ ,595454
+ ,590865
+ ,589379
+ ,584428
+ ,573100
+ ,567456
+ ,569028
+ ,620735
+ ,628884
+ ,628232
+ ,612117
+ ,595404
+ ,597141
+ ,593408
+ ,590072
+ ,579799
+ ,574205
+ ,572775
+ ,572942
+ ,619567
+ ,625809
+ ,619916
+ ,587625
+ ,565742
+ ,557274
+ ,560576
+ ,548854
+ ,531673
+ ,525919
+ ,511038
+ ,498662
+ ,555362
+ ,564591
+ ,541657
+ ,527070
+ ,509846
+ ,514258
+ ,516922
+ ,507561
+ ,492622
+ ,490243
+ ,469357
+ ,477580
+ ,528379
+ ,533590
+ ,517945
+ ,506174
+ ,501866
+ ,516141
+ ,528222
+ ,532638
+ ,536322
+ ,536535
+ ,523597
+ ,536214
+ ,586570
+ ,596594
+ ,580523
+ ,564478
+ ,557560
+ ,575093
+ ,580112
+ ,574761
+ ,563250
+ ,551531
+ ,537034
+ ,544686
+ ,600991
+ ,604378
+ ,586111
+ ,563668
+ ,548604
+ ,551174
+ ,555654)
> 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. 1.0.44 ()
> #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/1cy841323162333.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/2ltcn1323162333.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/3jspt1323162333.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  0.943952476  0.855584281  0.788065286  0.750328466
 [6]  0.734918623  0.714231567  0.683045987  0.649270271  0.637272783
[11]  0.654260009  0.693005129  0.702828147  0.626293242  0.521919044
[16]  0.438122304  0.385328443  0.356042585  0.322737165  0.281659759
[21]  0.240853620  0.221771478  0.231492258  0.261832567  0.264645706
[26]  0.187848104  0.085372735  0.004220145 -0.044639531 -0.069268680
[31] -0.096290886 -0.129297557 -0.161588247 -0.172236087 -0.155594287
[36] -0.119404141 -0.108443797 -0.171995484 -0.258603139 -0.325017675
[41] -0.359019575 -0.368552886 -0.378991421 -0.393934434 -0.407225186
[46] -0.399286041 -0.366384218 -0.316470586 -0.290856608
> (mypacf <- c(rpacf$acf))
 [1]  0.943952476 -0.325477591  0.254630799  0.106416826  0.121825708
 [6] -0.095579700  0.036317127  0.008635036  0.219117917  0.140025797
[11]  0.221652221 -0.294241368 -0.662101425  0.041944664  0.002632544
[16] -0.013384042  0.032585259  0.016630523  0.053203331 -0.005090880
[21]  0.032212495  0.001083772  0.004066158 -0.068491213 -0.272373312
[26]  0.012690401  0.010524072 -0.006281230  0.014134214  0.040911691
[31]  0.024284138 -0.042297321  0.023143208 -0.037255653 -0.006763713
[36] -0.005190305 -0.141611355  0.042126311 -0.032928563  0.006097051
[41]  0.002278518  0.042459802  0.018419630 -0.008449446  0.024869962
[46] -0.031546823 -0.032929301  0.007977197
> 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/4w27e1323162333.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/5l0zc1323162333.tab") 
> 
> try(system("convert tmp/1cy841323162333.ps tmp/1cy841323162333.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ltcn1323162333.ps tmp/2ltcn1323162333.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jspt1323162333.ps tmp/3jspt1323162333.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.987   0.165   1.160