R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(74.74,74.80,74.46,74.03,74.45,74.74,74.74,74.78,74.25,74.14,74.41,74.51,74.51,74.64,74.52,74.51,74.39,74.11,74.11,74.20,73.84,73.89,74.31,73.56,73.56,73.99,73.63,73.51,73.60,73.03,73.03,72.61,72.30,72.56,72.76,72.92,72.92,72.93,73.13,73.31,73.34,74.31,74.31,74.65,74.78,74.73,74.71,74.63,74.63,74.95,75.17,75.49,74.54,75.59,75.59,76.06,76.06,76.39,76.39,76.93,76.93,77.39,77.65,78.04,77.66,77.31,77.31,77.33,78.01,78.31,78.61,78.94,78.94,79.84,78.76,78.62,78.36,78.53,78.53,78.76,78.76,79.37,79.83,79.89)
> 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/1p5kp1394698414.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/2iasp1394698414.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/3f89n1394698414.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  0.95696706  0.91813308  0.87921071  0.84658922  0.81412055
 [7]  0.78594599  0.75371787  0.72724116  0.69277770  0.65300990  0.59653304
[13]  0.55274939  0.50384320  0.45836986  0.41260846  0.36910827  0.33213919
[19]  0.29645906  0.25770064  0.21625332  0.16177695  0.11575151  0.07017239
[25]  0.02811446 -0.01367354 -0.04657941 -0.08088022 -0.11047372 -0.14421238
[31] -0.17766191 -0.20847294 -0.22705184 -0.25961687 -0.28356715 -0.30510836
[37] -0.32239858 -0.33893180 -0.35659538 -0.37483568 -0.39073551 -0.40549643
[43] -0.41266481 -0.41790578 -0.41256744 -0.40777126 -0.40083238 -0.39184510
[49] -0.38149629
> (mypacf <- c(rpacf$acf))
 [1]  0.956967062  0.027870952 -0.018965565  0.054206344 -0.009038035
 [6]  0.033833095 -0.054395961  0.047685059 -0.098794551 -0.096193401
[11] -0.224248846  0.086300571 -0.092076866 -0.032264263 -0.022723651
[16] -0.028434143  0.078795917 -0.031421181  0.003815320 -0.056396495
[21] -0.167464102  0.011228835 -0.010098677 -0.027517761 -0.046394450
[26]  0.050429182 -0.062198335  0.038191103 -0.046170778 -0.006650535
[31]  0.047718506  0.048163147 -0.155617092  0.036497531  0.008642440
[36] -0.039356826 -0.007997165 -0.081778893  0.019333750 -0.054266480
[41] -0.004014871  0.057068603  0.056296317  0.051010047  0.001113925
[46]  0.005914622  0.047006154  0.031823542
> 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/4kupz1394698414.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/5unno1394698414.tab") 
> 
> try(system("convert tmp/1p5kp1394698414.ps tmp/1p5kp1394698414.png",intern=TRUE))
character(0)
> try(system("convert tmp/2iasp1394698414.ps tmp/2iasp1394698414.png",intern=TRUE))
character(0)
> try(system("convert tmp/3f89n1394698414.ps tmp/3f89n1394698414.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.925   0.552   3.473