R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(4143,4429,5219,4929,5761,5592,4163,4962,5208,4755,4491,5732,5731,5040,6102,4904,5369,5578,4619,4731,5011,5299,4146,4625,4736,4219,5116,4205,4121,5103,4300,4578,3809,5657,4248,3830,4736,4839,4411,4570,4104,4801,3953,3828,4440,4026,4109,4785,3224,3552,3940,3913,3681,4309,3830,4143,4087,3818,3380,3430,3458,3970,5260,5024,5634,6549,4676)
> 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/fisher/rcomp/tmp/1y9aq1355831012.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/fisher/rcomp/tmp/2d7nf1355831012.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/fisher/rcomp/tmp/33nja1355831012.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  0.464024608  0.385197849  0.451900494  0.219182084
 [6]  0.155773675  0.184602461  0.201247383  0.196596316  0.254539752
[11]  0.221184492  0.022917501  0.171673176  0.040853967 -0.030197637
[16] -0.007411443 -0.022897893 -0.010381401  0.024562604 -0.048559169
[21] -0.073536046 -0.029520031 -0.044466283 -0.111409531 -0.016028973
[26] -0.032556532 -0.033768117 -0.090922223 -0.091212921 -0.051396074
[31] -0.139196985 -0.143724319 -0.094138276 -0.143930201 -0.172326690
[36] -0.177194574 -0.128870464 -0.248191094 -0.237170442 -0.146773385
[41] -0.244350468 -0.213132767 -0.144934453 -0.198744928 -0.192617650
[46] -0.150441138 -0.180556757 -0.160218622 -0.010173024
> (mypacf <- c(rpacf$acf))
 [1]  4.640246e-01  2.164943e-01  2.826528e-01 -1.343127e-01 -5.818409e-02
 [6]  3.272389e-02  1.651895e-01  9.119710e-02  1.072771e-01 -3.442620e-02
[11] -2.774547e-01  1.441151e-01 -7.321241e-02  5.296814e-02 -1.386917e-01
[16] -1.563888e-02  5.952607e-05  1.035394e-01 -1.196532e-01 -6.490293e-02
[21]  1.701719e-02  2.306366e-02  5.620060e-02  2.123452e-02 -1.940141e-02
[26] -2.871165e-02 -1.279422e-01  1.473976e-03  1.271513e-01 -1.406634e-01
[31] -8.232212e-02 -4.117994e-03 -2.581648e-02 -1.029276e-01 -5.299279e-02
[36]  4.104405e-02 -1.186713e-01 -1.177375e-01  9.593738e-02  1.168255e-02
[41] -8.715467e-02 -3.409419e-02  4.334742e-04 -5.991436e-03  1.879393e-02
[46] -6.049224e-02  6.256947e-02  1.702046e-01
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4z1p11355831012.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/fisher/rcomp/tmp/5h2321355831012.tab") 
> 
> try(system("convert tmp/1y9aq1355831012.ps tmp/1y9aq1355831012.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d7nf1355831012.ps tmp/2d7nf1355831012.png",intern=TRUE))
character(0)
> try(system("convert tmp/33nja1355831012.ps tmp/33nja1355831012.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.918   0.582   2.504