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(383,349,317,401,285,377,380,347,414,406,487,475,566,604,764,725,585,797,740,587,719,621,677,636,591,636,748,571,475,758,554,597,521,597,658,482,567,605,653,512,653,498,520,606,601,608,732,585,800,721,689,689,777,681,836,594,662,835,702,630,857,847,820,801,900,763,897,687,682,844,687,671)
> 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/11ncb1420535559.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/2qe8h1420535559.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/3gkv31420535559.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 -0.530378205 -0.058493379  0.234196205 -0.031080461
 [6] -0.056269752  0.092295028 -0.205286906  0.108629540  0.186593693
[11] -0.315015056 -0.012233967  0.373011014 -0.425883951  0.221640757
[16] -0.034705509 -0.073940241  0.140763673 -0.110611253 -0.076022889
[21]  0.181851938 -0.069480049 -0.200061968  0.261214285 -0.077979386
[26] -0.143553038  0.213413612 -0.235179720  0.211783213 -0.077439684
[31] -0.150121816  0.191409049  0.021320681 -0.129452858  0.024931866
[36]  0.130804409 -0.137796224  0.133944167 -0.087942608 -0.078444498
[41]  0.276808450 -0.216039440 -0.048303090  0.152169704 -0.028442570
[46] -0.099096446  0.092931211 -0.005496258 -0.042067465
> (mypacf <- c(rpacf$acf))
 [1] -0.530378205 -0.472791027 -0.111555349  0.131176988  0.187670899
 [6]  0.239277468 -0.196110816 -0.348245183  0.052037560  0.076833362
[11] -0.183503586  0.166900257 -0.182803847  0.017553349  0.008128406
[16]  0.015838375  0.092243323 -0.159425854 -0.128906635 -0.041563467
[21] -0.034512620 -0.123971171  0.008450187 -0.009750886 -0.003293872
[26]  0.003074875 -0.209590107  0.045106028 -0.119073333 -0.162053424
[31]  0.030370700  0.010456598  0.147808847  0.062668047 -0.047819222
[36] -0.096732364 -0.007297873  0.014080788  0.010233385 -0.057147834
[41]  0.035071143 -0.016514272 -0.131666503  0.099454145 -0.045761919
[46]  0.020624218  0.142484928  0.012669872
> 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/4oz7m1420535559.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/5x71w1420535559.tab") 
> 
> try(system("convert tmp/11ncb1420535559.ps tmp/11ncb1420535559.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qe8h1420535559.ps tmp/2qe8h1420535559.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gkv31420535559.ps tmp/3gkv31420535559.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.166   0.259   1.433