R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(4.69,4.69,4.69,4.69,4.69,4.69,4.69,4.73,4.78,4.79,4.79,4.8,4.8,4.81,5.16,5.26,5.29,5.29,5.29,5.3,5.3,5.3,5.3,5.3,5.3,5.3,5.3,5.35,5.44,5.47,5.47,5.48,5.48,5.48,5.48,5.48,5.48,5.48,5.5,5.55,5.57,5.58,5.58,5.58,5.59,5.59,5.59,5.55,5.61,5.61,5.61,5.63,5.69,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.71,5.74,5.77,5.79,5.79,5.8,5.8,5.8,5.8)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> 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. 1.2.291 ()
> #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/fisher/rcomp/tmp/1y0le1363527713.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/fisher/rcomp/tmp/2fnbk1363527713.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/fisher/rcomp/tmp/3q7fn1363527713.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  0.955186290  0.904416906  0.851891362  0.798591362
 [6]  0.744988063  0.690664848  0.635233277  0.582068412  0.533360608
[11]  0.485296365  0.436654008  0.387682295  0.336812619  0.282821184
[16]  0.251225641  0.225793627  0.202176857  0.177872895  0.153601655
[21]  0.130421199  0.108638763  0.086795121  0.064624245  0.041569834
[26]  0.018899016 -0.008459745 -0.037072906 -0.062489770 -0.080724435
[31] -0.096947515 -0.113748710 -0.129600924 -0.144685348 -0.156901316
[36] -0.170585599 -0.184629840 -0.199546707 -0.216557878 -0.234784059
[41] -0.249639419 -0.263255528 -0.276042642 -0.288862479 -0.300508817
[46] -0.307785962 -0.313165449 -0.318621291 -0.327177379
> (mypacf <- c(rpacf$acf))
 [1]  9.551863e-01 -9.089272e-02 -4.254308e-02 -3.506716e-02 -3.191267e-02
 [6] -3.846490e-02 -4.387803e-02 -5.918364e-03  1.527423e-02 -3.109094e-02
[11] -4.154940e-02 -3.763048e-02 -5.734159e-02 -7.328969e-02  2.249328e-01
[16]  1.675570e-02 -1.766845e-02 -4.170110e-02 -2.822923e-02 -1.966977e-02
[21] -2.135577e-02 -1.971205e-02 -2.957273e-03 -3.105932e-02 -2.667135e-02
[26] -9.070978e-02 -5.354948e-02 -1.692280e-02  1.195538e-01  1.515412e-02
[31] -3.061609e-02 -2.800890e-02 -3.062777e-02  7.685994e-05 -4.443282e-02
[36] -1.811280e-02 -1.709124e-02 -5.309363e-02 -4.139239e-02 -2.506916e-02
[41] -4.400470e-02 -2.446002e-02  3.044060e-02  1.376278e-02  1.788289e-02
[46] -2.148091e-02 -3.904896e-02 -4.942559e-02
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/412m51363527713.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/fisher/rcomp/tmp/5yksg1363527713.tab") 
> 
> try(system("convert tmp/1y0le1363527713.ps tmp/1y0le1363527713.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fnbk1363527713.ps tmp/2fnbk1363527713.png",intern=TRUE))
character(0)
> try(system("convert tmp/3q7fn1363527713.ps tmp/3q7fn1363527713.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.005   0.293   2.279