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(340,307,380,347,313,333,347,333,387,307,353,407,307,253,380,320,353,353,387,280,387,307,347,427,253,240,407,293,347,360,387,240,333,353,313,440,273,240,407,240,360,373,387,320,373,373,260,420,253,293,413,207,333,440,280,367,380,373,193,373,213,293,407,167,340,447,233,393,333,353,200,413,187,300,413,213,373,453,247,447,340,320,187,380,160,307,400,213,380,453,260,467,380,300,180,427,153,327,393,207,380,440,247,400,360,340,220,393)
> 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/wessaorg/rcomp/tmp/1qyto1407246096.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/2zn001407246096.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/3vdd71407246096.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 -0.40526052 -0.04098498  0.37634876 -0.27946468 -0.21510545
 [7]  0.25465228 -0.21244047 -0.22032326  0.32457896 -0.03479387 -0.34301053
[13]  0.83033439 -0.39913898 -0.01503560  0.35188953 -0.31446899 -0.14471422
[19]  0.20565025 -0.19883017 -0.13255829  0.26818783 -0.05683535 -0.22042042
[25]  0.61654876 -0.37795071  0.01169121  0.33025945 -0.34806034 -0.06079337
[31]  0.16041737 -0.18593714 -0.06532743  0.23999769 -0.08264832 -0.09698525
[37]  0.42611246 -0.31248594  0.01185056  0.28328188 -0.35199282  0.01332639
[43]  0.10488058 -0.16622757 -0.02510634  0.19064713 -0.10635384 -0.01853726
[49]  0.25076308
> (mypacf <- c(rpacf$acf))
 [1] -0.405260520 -0.245549094  0.326150303  0.013143932 -0.407594952
 [6] -0.180141325 -0.030533049 -0.235143850 -0.062336463  0.199176452
[11] -0.320070949  0.668892842  0.035120463  0.085547310 -0.083990736
[16] -0.049932224  0.110215068 -0.105874842  0.034372736  0.087227003
[21]  0.039561362 -0.105698781  0.142208048 -0.173834801 -0.027447471
[26] -0.101582071  0.134430298  0.025246335 -0.069286848 -0.070126478
[31]  0.039780257  0.046131123  0.026950070  0.009577813  0.076352807
[36] -0.023498126  0.058457484 -0.035449587 -0.011253194  0.006751522
[41] -0.003815282 -0.038153210 -0.018327579 -0.016126374 -0.090728702
[46] -0.062982804 -0.123484163 -0.081513025
> 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/4feqd1407246096.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/52g891407246096.tab") 
> 
> try(system("convert tmp/1qyto1407246096.ps tmp/1qyto1407246096.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zn001407246096.ps tmp/2zn001407246096.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vdd71407246096.ps tmp/3vdd71407246096.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.172   0.212   1.388