R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(28.33,28.67,28.81,28.99,29.16,29.25,29.25,29.38,29.48,29.65,29.69,29.73,29.81,30.05,30.29,30.37,30.50,30.67,30.72,30.73,30.76,30.82,30.84,30.86,30.92,30.95,30.97,30.99,31.09,31.18,31.19,31.20,31.31,31.34,31.35,31.36,31.37,31.37,31.39,31.39,31.42,31.47,31.48,31.51,31.54,31.55,31.55,31.57,31.66,31.68,31.70,31.70,31.73,31.74,31.75,31.78,31.80,31.82,31.82,31.90)
> 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/1eu5k1395086653.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/2x0bt1395086653.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/3xu911395086653.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  0.472785685  0.295529944  0.302554131  0.342953274
 [6]  0.180121114  0.193009258  0.170322735  0.224731190  0.121886427
[11]  0.144845405  0.221851972  0.358950962  0.265214294  0.120493298
[16]  0.210978212  0.170769837 -0.054576180 -0.071550452  0.014750923
[21]  0.003284686 -0.103195147 -0.158760669 -0.082512623 -0.067453940
[26] -0.084807473 -0.131784195 -0.006944083 -0.048441945 -0.151409238
[31] -0.145388633 -0.022870764 -0.142513866 -0.183259040 -0.139008941
[36] -0.135707345 -0.180892789 -0.195527313 -0.192569968 -0.130366244
[41] -0.146996264 -0.182904404 -0.180944808 -0.145691943 -0.162146919
[46] -0.120201559 -0.079370643 -0.037816213 -0.106235760
> (mypacf <- c(rpacf$acf))
 [1]  0.472785685  0.092731589  0.171404103  0.175686314 -0.094280003
 [6]  0.089250881 -0.011330505  0.115133148 -0.058351197  0.051122120
[11]  0.134641179  0.222384671  0.028665938 -0.160783495  0.111016949
[16] -0.117107742 -0.235543869 -0.067978207 -0.012916207  0.012653884
[21] -0.089137460 -0.120926833 -0.044403313 -0.072277565 -0.010212989
[26] -0.086650971  0.110635617 -0.040725542  0.031945329  0.081274665
[31]  0.048726022 -0.062038774  0.006213729  0.086953094 -0.099485015
[36]  0.003408242 -0.012172593 -0.049193250 -0.033768492 -0.100267589
[41] -0.009185429 -0.106314993 -0.116671388 -0.005745493  0.108746441
[46] -0.014229027  0.065643857  0.062847439
> 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/4qqy81395086653.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/5l3qt1395086653.tab") 
> 
> try(system("convert tmp/1eu5k1395086653.ps tmp/1eu5k1395086653.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x0bt1395086653.ps tmp/2x0bt1395086653.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xu911395086653.ps tmp/3xu911395086653.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.016   0.592   3.591