R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(123.2,136.9,146.8,149.6,146.5,157,147.9,133.6,128.7,100.8,91.8,89.3,96.7,91.6,93.3,93.3,101,100.4,86.9,83.9,80.3,87.7,92.7,95.5,92,87.4,86.8,83.7,85,81.7,90.9,101.5,113.8,120.1,122.1,132.5,140,149.4,144.3,154.4,151.4,145.5,136.8,146.6,145.1,133.6,131.4,127.5,130.1,131.1,132.3,128.6,125.1,128.7,156.1,163.2,159.8,157.4,156.2,152.5,149.4,145.9,144.8,135.9,137.6,136,117.7,111.5,107.8,107.3,102.6,101)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> 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. 1.2.291 ()
> #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/1md751425485305.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/2d0l31425485305.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/3jqzf1425485305.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  0.316118225  0.125424670  0.049742335  0.097614373
 [6] -0.030494690 -0.087733357 -0.060746815 -0.191301336 -0.042098540
[11] -0.018022646  0.129021461 -0.237797799 -0.198082674 -0.064579579
[16]  0.041066724  0.007312427 -0.018205397  0.121595984  0.060296700
[21]  0.077901557  0.048072056  0.008085736 -0.053518949 -0.098894186
[26] -0.074751234 -0.162061279 -0.068542823 -0.103585990 -0.075983251
[31] -0.138509869  0.006476179  0.093723885  0.032311955  0.002789074
[36] -0.047572892 -0.070855852 -0.032741279  0.141588035 -0.009885282
[41] -0.067889356 -0.004899721  0.077372936 -0.002036226 -0.133354598
[46] -0.194997553 -0.085249466 -0.077444309  0.012024631
> (mypacf <- c(rpacf$acf))
 [1]  0.316118225  0.028324418  0.002515694  0.086827895 -0.096487061
 [6] -0.071665850 -0.005027399 -0.191027846  0.098166631  0.007614033
[11]  0.143194623 -0.346360423 -0.078102211  0.041674731  0.062702213
[16]  0.026284387 -0.003661652  0.096201344  0.015781236 -0.095839236
[21]  0.015814570 -0.079116802  0.126207610 -0.145520266 -0.108378937
[26] -0.148349476  0.098522996 -0.050924479 -0.096700503 -0.102187630
[31]  0.195259580  0.062512368 -0.053705405 -0.188928752  0.040828869
[36] -0.146681556  0.074042570 -0.007715007 -0.029600925 -0.046725055
[41]  0.061255159 -0.160645762 -0.040248532 -0.093298158 -0.018904761
[46]  0.004188729 -0.063265995 -0.025541795
> 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/4hgix1425485305.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/5pbit1425485305.tab") 
> 
> try(system("convert tmp/1md751425485305.ps tmp/1md751425485305.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d0l31425485305.ps tmp/2d0l31425485305.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jqzf1425485305.ps tmp/3jqzf1425485305.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.199   0.228   1.433