R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(102.43,102.43,102.43,102.43,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,108.1,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,115.57,115.57,115.57,115.57,115.57,115.57,115.57,115.57,115.57,115.57,115.57,117.3,117.3,118.39,118.39,118.39,118.39,118.39,118.39,118.39,118.39,118.39,118.39,121.18,123.21,123.21,123.21,123.21,123.21,123.21,123.21,123.21)
> 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/1z09u1384782748.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/2tysp1384782748.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/3uz7m1384782748.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  0.953950041  0.904478359  0.854358443  0.804238526
 [6]  0.760528104  0.716817683  0.673107262  0.629396840  0.592836544
[11]  0.566103267  0.538324569  0.508236638  0.466818835  0.423239684
[16]  0.379660534  0.336081384  0.306624851  0.281151621  0.255678390
[21]  0.234044390  0.212410389  0.196869845  0.181329300  0.162423411
[26]  0.136831727  0.110224599  0.083617471  0.057010343  0.040904648
[31]  0.024798954  0.008693259 -0.007412436 -0.020841236 -0.034270037
[36] -0.047698837 -0.065738852 -0.088337863 -0.112023511 -0.135709159
[41] -0.159394808 -0.173267048 -0.187139288 -0.201011528 -0.214883768
[46] -0.219210767 -0.223537766 -0.228518947 -0.238600897
> (mypacf <- c(rpacf$acf))
 [1]  0.953950041 -0.061595499 -0.031861138 -0.026573364  0.043867841
 [6] -0.030064421 -0.026404675 -0.026458051  0.058186364  0.080619898
[11] -0.039738591 -0.047939508 -0.137766837 -0.029771470 -0.028630968
[16] -0.032627347  0.121029416  0.029035453 -0.017322012  0.010181325
[21] -0.030428010  0.026735984 -0.024016335 -0.051280894 -0.062425683
[26]  0.017048923 -0.015770783 -0.028687540  0.062808995 -0.031289221
[31] -0.013475856 -0.043801012  0.023560068 -0.031414316 -0.015465348
[36] -0.058611327 -0.043826126 -0.000307458 -0.022435423 -0.044852486
[41]  0.052892569 -0.022985023 -0.025900177 -0.043156492  0.105871167
[46] -0.031325335 -0.025904764 -0.072743416
> 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/4aiwp1384782748.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/5cjcb1384782748.tab") 
> 
> try(system("convert tmp/1z09u1384782748.ps tmp/1z09u1384782748.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tysp1384782748.ps tmp/2tysp1384782748.png",intern=TRUE))
character(0)
> try(system("convert tmp/3uz7m1384782748.ps tmp/3uz7m1384782748.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.362   0.512   2.849