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(3844.49,3720.98,3674.4,3857.62,3801.06,3504.37,3032.6,3047.03,2962.34,2197.82,2014.45,1862.83,1905.41,1810.99,1670.07,1864.44,2052.02,2029.6,2070.83,2293.41,2443.27,2513.17,2466.92,2502.66,2539.91,2482.6,2626.15,2656.32,2446.66,2467.38,2462.32,2504.58,2579.39,2649.24,2636.87,2613.94,2634.01,2711.94,2646.43,2717.79,2701.54,2572.98,2488.92,2204.91,2123.99,2149.1,2036.71,2048.32,2159.56,2267.79,2313.55,2247.3,2134.43,2114,2236.94,2345.39,2422.4,2385.96,2378.17,2457.13,2527.67,2530.03,2604.92,2596.8,2713.2,2574.82,2611.98,2768.46,2785.61,2859.27,2880.53,2824.5)
> 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/16lgg1413815285.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/2f2831413815285.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/37wto1413815285.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  0.306206425  0.035464717  0.245244666  0.275447788
 [6]  0.180514007 -0.175567758 -0.079925555  0.099388990 -0.097192110
[11] -0.217459695 -0.132023755 -0.059074691 -0.033602878 -0.086180005
[16] -0.066298643  0.020109391 -0.069778921 -0.020598260  0.075473964
[21] -0.083335979 -0.069244753 -0.005287498 -0.052594442 -0.072111247
[26] -0.096772279 -0.126098288 -0.080751208 -0.063385828  0.090951102
[31]  0.043098365 -0.033921897  0.084711877  0.102911742  0.156752997
[36]  0.111437447  0.047968850  0.161674634  0.064233517 -0.061203473
[41] -0.016145639  0.014320925  0.016613576  0.031312718 -0.015834519
[46] -0.055869521 -0.018115553  0.002983963 -0.005810667
> (mypacf <- c(rpacf$acf))
 [1]  0.306206425 -0.064329328  0.280762497  0.133094025  0.098093076
 [6] -0.345670217 -0.007608109 -0.006309003 -0.082077840 -0.083127015
[11]  0.021813475 -0.068152568  0.062899131  0.050426500  0.003000442
[16] -0.026455286 -0.115871639  0.033160269  0.066663420 -0.144635723
[21] -0.021342618 -0.005975080 -0.089356349 -0.025215767  0.047666750
[26] -0.172561487 -0.053118056  0.059756950  0.248982754 -0.041328916
[31]  0.010099681 -0.036184219 -0.032803454  0.097031094  0.111685586
[36] -0.043387607 -0.032301845 -0.110868839 -0.007047397  0.025040228
[41]  0.032488642  0.017906887  0.146747035 -0.010226629 -0.070533602
[46]  0.002230875 -0.031512841 -0.111756681
> 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/44a8n1413815285.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/5eu0s1413815285.tab") 
> 
> try(system("convert tmp/16lgg1413815285.ps tmp/16lgg1413815285.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f2831413815285.ps tmp/2f2831413815285.png",intern=TRUE))
character(0)
> try(system("convert tmp/37wto1413815285.ps tmp/37wto1413815285.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.209   0.205   1.422