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(59400,57200,60500,48400,62700,61600,66000,68200,75900,66000,62700,78100,66000,49500,58300,44000,61600,50600,67100,60500,63800,71500,70400,83600,60500,50600,56100,40700,58300,45100,63800,60500,53900,77000,69300,79200,59400,55000,49500,40700,53900,48400,66000,63800,55000,73700,68200,88000,70400,42900,42900,42900,50600,50600,68200,62700,56100,70400,64900,93500,73700,42900,45100,37400,51700,59400,74800,73700,59400,69300,61600,88000,67100,53900,48400,36300,53900,64900,75900,71500,52800,75900,59400,91300,75900,55000,50600,34100,53900,51700,78100,78100,59400,77000,57200,89100,75900,56100,42900,29700,58300,56100,73700,84700,62700,70400,52800,91300)
> 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/1l5lg1439045089.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/2vij01439045089.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/318v31439045089.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 -0.34099026  0.16117122 -0.18722410 -0.33959598  0.37095515
 [7] -0.34394957  0.41811068 -0.28759624 -0.18407928  0.13441850 -0.31309345
[13]  0.78955157 -0.25518104  0.19065720 -0.16484408 -0.35056914  0.33773501
[19] -0.30827381  0.37650662 -0.22422802 -0.15781700  0.10351417 -0.27386725
[25]  0.60242437 -0.13876351  0.17684239 -0.13654251 -0.30831234  0.24726300
[31] -0.25777595  0.30535560 -0.15311370 -0.11856407  0.09306592 -0.26340316
[37]  0.50136785 -0.07654881  0.09898497 -0.08370534 -0.25128367  0.19095897
[43] -0.25392886  0.27663020 -0.10162638 -0.07910882  0.08589391 -0.25104265
[49]  0.39428607
> (mypacf <- c(rpacf$acf))
 [1] -0.340990263  0.050804075 -0.133570111 -0.514820883  0.179815217
 [6] -0.220958197  0.076756226 -0.234548990 -0.434092504 -0.217000293
[11] -0.396936872  0.445035918  0.108652141  0.043625259 -0.004305512
[16] -0.015357294  0.049770608  0.089723593 -0.104653523 -0.051051396
[21] -0.005491383 -0.041121740  0.039510049 -0.115361413  0.072225167
[26]  0.043009008 -0.018900953  0.066735686 -0.040516409 -0.017416444
[31] -0.047432673 -0.044357007  0.014553393  0.080648596 -0.100601093
[36]  0.127453823  0.068868463 -0.162689084 -0.038457603  0.054242415
[41]  0.071862454 -0.132689471 -0.007348424  0.009600314  0.124014402
[46]  0.053238359 -0.053354514 -0.098083669
> 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/4pwnx1439045089.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/5ic7x1439045089.tab") 
> 
> try(system("convert tmp/1l5lg1439045089.ps tmp/1l5lg1439045089.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vij01439045089.ps tmp/2vij01439045089.png",intern=TRUE))
character(0)
> try(system("convert tmp/318v31439045089.ps tmp/318v31439045089.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.189   0.282   1.454