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(1.3,1.2,1.1,1.4,1.5,1.4,1.1,1.1,1,1.4,1.3,1.2,1.5,1.6,1.8,1.5,1.3,1.6,1.6,1.8,1.8,1.6,1.8,2,1.3,1.1,1,1.2,1.2,1.3,1.3,1.4,1.1,0.9,1,1.1,1.4,1.5,1.8,1.8,1.8,1.7,1.5,1.1,1.3,1.6,1.9,1.9,2,2.2,2.2,2,2.3,2.6,3.2,3.2,3.1,2.8,2.3,1.9,1.9,2,2,1.8,1.6,1.4,0.2,0.3,0.4,0.7,1,1.1,0.8,0.8,1,1.1,1,0.8,1.6,1.5,1.6,1.6,1.6,1.9,2,1.9,2,2.1,2.3,2.3,2.6,2.6,2.7,2.6,2.6,2.4,2.5,2.5,2.5,2.4,2.1,2.1,2.3,2.3,2.3,2.9,2.8,2.9,3,3,2.9,2.6,2.8,2.9,3.1,2.8,2.4,1.6,1.5,1.7,1.4,1.1,0.8,1.2,0.8,0.9,0.9,1,0.9,1.1,1,0.7)
> 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/wessaorg/rcomp/tmp/1yuuz1425306105.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/29kjy1425306105.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/3v18q1425306105.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  0.918747986  0.823494531  0.729211764  0.650496776
 [6]  0.577355891  0.506406408  0.433081681  0.347748364  0.248288594
[11]  0.123752713  0.004467372 -0.098566296 -0.131166243 -0.152640044
[16] -0.169635444 -0.182726029 -0.202699676 -0.216790365 -0.246970945
[21] -0.273232004 -0.281447087 -0.268270263 -0.248026535 -0.229165302
[26] -0.224996758 -0.225468397 -0.223998660 -0.238692352 -0.229280621
[31] -0.213199086 -0.181498296 -0.149275393 -0.115596458 -0.089881579
[36] -0.083381912 -0.086875922 -0.094017365 -0.092959436 -0.085481727
[41] -0.051758670 -0.028749952 -0.008366503 -0.007095316 -0.004838733
[46] -0.002582151 -0.012547415  0.008622880  0.051832207
> (mypacf <- c(rpacf$acf))
 [1]  0.918747986 -0.132155539 -0.038786583  0.045600964 -0.028010238
 [6] -0.036811849 -0.056743367 -0.123959293 -0.142299925 -0.238536491
[11] -0.072516962 -0.035610820  0.343127425 -0.018287549  0.015917605
[16]  0.069076046 -0.056959046  0.027123246 -0.188118120 -0.124096506
[21] -0.039646818 -0.087426146  0.003993711  0.002947224  0.080567325
[26]  0.026541887  0.041275786 -0.079403940  0.112446982 -0.004529938
[31] -0.066053578 -0.049734202  0.046572947 -0.026119976 -0.118271745
[36] -0.104247678 -0.056301547 -0.015142387  0.008584181  0.113202594
[41]  0.089056231  0.092812528 -0.028197941  0.102569994  0.030932280
[46] -0.156636122  0.056749756  0.006541948
> 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/4onir1425306105.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/5tv4b1425306105.tab") 
> 
> try(system("convert tmp/1yuuz1425306105.ps tmp/1yuuz1425306105.png",intern=TRUE))
character(0)
> try(system("convert tmp/29kjy1425306105.ps tmp/29kjy1425306105.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v18q1425306105.ps tmp/3v18q1425306105.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.275   0.206   1.490