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(3862.5,3875.7,3875.9,3877.7,3880.4,3883.4,3884.2,3884.8,3894.9,3903.3,3911.2,3928.9,3945.6,3965.7,3992.3,4008.7,4014.8,4020.6,4037.5,4058.5,4082.3,4102.4,4127.1,4144.4,4161,4168.2,4178.3,4174.1,4165.7,4167.9,4158.3,4158.3,4143.7,4157.5,4164.8,4173.9,4181.2,4190.7,4206.6,4222.1,4245.8,4255.4,4266.1,4273.6,4282.1,4299.8,4315.7,4331.7,4348.4,4367.8,4387.2,4410.9,4436,4453.8,4469.1,4472,4458.2,4449,4441.5,4445.7,4453.9,4469.7,4487.5,4504,4524.1,4540.5,4548.4,4554.2,4558,4557.5,4554.5,4550,4543.8,4538.2,4543.3,4545.1)
> 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/196ou1425482036.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/2byi61425482036.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/3zsv21425482036.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  0.719717920  0.565689252  0.283032960  0.089024091
 [6] -0.084755578 -0.236869325 -0.242433126 -0.330861532 -0.228001067
[11] -0.180585692 -0.060024617 -0.010743729  0.027373797  0.047165181
[16] -0.008279017 -0.119428450 -0.220889407 -0.273737665 -0.260345296
[21] -0.251236237 -0.209142571 -0.153839265 -0.076193821  0.046834969
[26]  0.186615654  0.255537152  0.235288662  0.262693582  0.199587149
[31]  0.135972181  0.046589053 -0.026844364 -0.115386072 -0.139062623
[36] -0.151196285 -0.121218536 -0.048134983  0.039081739  0.146093394
[41]  0.184145752  0.185789154  0.093509812  0.052611850 -0.021665060
[46] -0.050889889 -0.081900685 -0.096540351 -0.089084468
> (mypacf <- c(rpacf$acf))
 [1]  0.719717920  0.098951789 -0.324824145 -0.105348131 -0.047734987
 [6] -0.162347370  0.121845927 -0.198383271  0.133274467  0.044164394
[11] -0.006903274 -0.061471450 -0.032359344 -0.051993978 -0.063380552
[16] -0.302224106 -0.022435341  0.005982438  0.082266128 -0.114471022
[21] -0.099816067 -0.035490157  0.056599587  0.032678253  0.159391981
[26] -0.127351364 -0.096007814  0.182942989 -0.058166145 -0.090377506
[31]  0.041985124 -0.091192435 -0.095983081  0.062018061 -0.118396527
[36]  0.092852036  0.105769993  0.007483221  0.008311032 -0.035018782
[41] -0.016266245 -0.033679304  0.008553582  0.031253820  0.051802204
[46]  0.089590966  0.009663072 -0.050683236
> 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/4tvpk1425482036.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/5foml1425482036.tab") 
> 
> try(system("convert tmp/196ou1425482036.ps tmp/196ou1425482036.png",intern=TRUE))
character(0)
> try(system("convert tmp/2byi61425482036.ps tmp/2byi61425482036.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zsv21425482036.ps tmp/3zsv21425482036.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.195   0.252   1.453