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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(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)
> 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/1z7r21425298668.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/2qbo11425298668.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/3at2p1425298668.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]  1.00000000  0.92442211  0.81822136  0.70596966  0.61968735  0.55486749
 [7]  0.50212093  0.44138268  0.35838854  0.25700568  0.15021877  0.05451157
[13] -0.02857192 -0.05336548 -0.06915231 -0.07760867 -0.09967519 -0.13099862
[19] -0.15948422 -0.19486783 -0.22472230 -0.24095232 -0.25462329 -0.26791898
[25] -0.27620021 -0.28626849 -0.28707986 -0.28275168 -0.27894532 -0.26715442
[31] -0.26333376 -0.25631429 -0.24736122 -0.23415856 -0.20872892 -0.20169514
[37] -0.20265305 -0.21441903 -0.22539870 -0.23908397 -0.22176394 -0.20612017
[43] -0.18700596 -0.16645853 -0.14308756 -0.12615711 -0.12182893 -0.09639214
[49] -0.04881739
> (mypacf <- c(rpacf$acf))
 [1]  0.9244221083 -0.2498207835 -0.0618356611  0.1329283747  0.0319934647
 [6] -0.0158818904 -0.1010423084 -0.1589164518 -0.1159811540 -0.0773722220
[11] -0.0330775554 -0.0687915007  0.3137435628 -0.1132725270  0.0227465320
[16] -0.0190960816 -0.0404423314  0.0300719163 -0.1891643972 -0.0823902709
[21]  0.0045356436 -0.1048637908 -0.0221757985  0.0002144906  0.1002296818
[26]  0.0230628877  0.0487671396 -0.0869553033  0.0457960662 -0.0685205558
[31] -0.1170228277 -0.0303797618 -0.0152557682  0.0409827358 -0.2126035328
[36] -0.0095832777 -0.0129067028  0.0331692047 -0.0794880116  0.1709068937
[41] -0.0585937461 -0.0435446072  0.0937218946 -0.0273601195 -0.0714197612
[46] -0.0392434310  0.0244957327  0.1490494352
> 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/4c39a1425298668.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/5o0x61425298668.tab") 
> 
> try(system("convert tmp/1z7r21425298668.ps tmp/1z7r21425298668.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qbo11425298668.ps tmp/2qbo11425298668.png",intern=TRUE))
character(0)
> try(system("convert tmp/3at2p1425298668.ps tmp/3at2p1425298668.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.252   0.218   1.478