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(78.7,75.7,77.1,86.1,86.8,86.3,91.5,90.7,78.2,73,73.7,77.3,67.5,72.7,76.6,82.4,82.3,86.3,93,88.8,96.9,103.9,115.7,112.8,114.7,118,129.3,137,156,166.2,167.8,144.3,126,90.4,67.5,52.4,54.6,52.9,59.1,63.3,73.8,87.6,81.8,90.7,86.3,93.6,98,94.3,97.6,94.2,100.2,106.7,95.7,94.6,94.7,96.2,96.3,103.3,106.8,113.7,117.4,123.6,137.6,147.4,137.2,133.8,136.7,127.3,128.7,127,133.7,132)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '60'
> #'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/196xj1334051206.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/2q9z51334051206.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/3muw81334051206.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]  1.00000000  0.92814769  0.79782929  0.63047164  0.45594939  0.28738300
 [7]  0.14296342  0.03901215 -0.04323081 -0.12035323 -0.17402914 -0.20565457
[13] -0.22920407 -0.25057673 -0.25587559 -0.25140896 -0.24364594 -0.22941809
[19] -0.20915790 -0.18415145 -0.16969439 -0.15818112 -0.15041467 -0.14484957
[25] -0.15801169 -0.16521829 -0.18237383 -0.18340532 -0.16342747 -0.11539555
[31] -0.04059628  0.03889343  0.12302046  0.20119067  0.25166663  0.27970179
[37]  0.29194252  0.30140763  0.29965039  0.28838909  0.26253969  0.22246415
[43]  0.16917991  0.11111063  0.06327456  0.01913076 -0.01920160 -0.04814488
[49] -0.07495752 -0.10495939 -0.13348909 -0.14779912 -0.15165417 -0.15673651
[55] -0.16279148 -0.15961443 -0.15598922 -0.15660800 -0.15381327 -0.14574923
[61] -0.13673315
> (mypacf <- c(rpacf$acf))
 [1]  0.928147690 -0.459275224 -0.218182208 -0.015730732 -0.049065516
 [6]  0.032791037  0.108196308 -0.156819256 -0.204563862  0.143746306
[11]  0.036854026 -0.146956538 -0.058093088  0.084088840 -0.095428454
[16] -0.019666569  0.088336506 -0.111606174 -0.055270554 -0.019584823
[21]  0.000277716 -0.105779697  0.032194007 -0.184321937  0.072449634
[26] -0.164241775  0.187302048  0.126268648  0.017645341  0.040013762
[31] -0.041413449  0.093907411 -0.002783132 -0.066044777  0.008170038
[36]  0.078208346  0.081748984  0.008489154 -0.018613539 -0.170943397
[41]  0.003779113  0.059980356  0.111568742 -0.027027077 -0.028123301
[46] -0.038260576  0.057881087 -0.106812659  0.006963677 -0.031724401
[51]  0.108296551 -0.066783082 -0.107071855  0.010903084  0.026809161
[56]  0.009244009  0.013816405  0.003953637  0.005957557 -0.036771161
> 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/4e0871334051206.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/5dqq91334051206.tab") 
> 
> try(system("convert tmp/196xj1334051206.ps tmp/196xj1334051206.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q9z51334051206.ps tmp/2q9z51334051206.png",intern=TRUE))
character(0)
> try(system("convert tmp/3muw81334051206.ps tmp/3muw81334051206.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.007   0.219   1.232