R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1.4718,1.4748,1.5527,1.5751,1.5557,1.5553,1.577,1.4975,1.4369,1.3322,1.2732,1.3449,1.3239,1.2785,1.305,1.319,1.365,1.4016,1.4088,1.4268,1.4562,1.4816,1.4914,1.4614,1.4272,1.3686,1.3569,1.3406,1.2565,1.2209,1.277,1.2894,1.3067,1.3898,1.3661,1.322,1.336,1.3649,1.3999,1.4442,1.4349,1.4388,1.4264,1.4343,1.377,1.3706,1.3556,1.3179,1.2905,1.3224,1.3201,1.3162,1.2789,1.2526,1.2288,1.24,1.2856,1.2974,1.2828,1.3119,1.3288,1.3359,1.2964,1.3026,1.2982,1.3189,1.308,1.331,1.3348,1.3635,1.3493,1.3704,1.361,1.3658,1.3823,1.3812,1.3732,1.3592,1.3539,1.3316,1.2901,1.2673,1.2472,1.2331)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> 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/17aak1445715406.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/264891445715406.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/3myt21445715406.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  0.291139076  0.013380603  0.100944178 -0.008627124
 [6] -0.125760022 -0.048911742 -0.308541968 -0.234942537 -0.125663204
[11] -0.079260924 -0.186400603 -0.117035765 -0.102481339 -0.089471872
[16]  0.055725984  0.222419447  0.083352092  0.214301909  0.273313638
[21]  0.069081380 -0.068274095  0.031679862 -0.154941771 -0.126904770
[26] -0.071027896 -0.059315169  0.028267545  0.044198755 -0.089299357
[31] -0.053361309 -0.048600281 -0.087966003 -0.059612851  0.075123846
[36]  0.146719761  0.064932056  0.105962646  0.102472978  0.070168464
[41]  0.008756008 -0.033631950 -0.102522915 -0.013452880  0.015971325
[46]  0.047544298 -0.078794382 -0.076612764 -0.039991157
> (mypacf <- c(rpacf$acf))
 [1]  0.291139076 -0.077992125  0.131312649 -0.087224066 -0.097526238
 [6]  0.006284312 -0.342118074 -0.015980955 -0.119324764  0.017822045
[11] -0.204263582 -0.101556484 -0.126648608 -0.196417358  0.034669046
[16]  0.061408346 -0.051365065  0.122866874  0.045079219 -0.095797039
[21] -0.180855000  0.005484972 -0.157518654 -0.026061832 -0.047600771
[26]  0.043359892  0.146960270 -0.099443814 -0.016784302 -0.078146313
[31] -0.091450058 -0.147560685 -0.066810795  0.037761488  0.042183858
[36] -0.058918777  0.021823688 -0.062343095  0.127708704 -0.078295657
[41]  0.036648653 -0.068075749  0.003099639 -0.007264220  0.035036038
[46] -0.150625326  0.009276706  0.090469804
> 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/4xj3j1445715406.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/5abbv1445715406.tab") 
> 
> try(system("convert tmp/17aak1445715406.ps tmp/17aak1445715406.png",intern=TRUE))
character(0)
> try(system("convert tmp/264891445715406.ps tmp/264891445715406.png",intern=TRUE))
character(0)
> try(system("convert tmp/3myt21445715406.ps tmp/3myt21445715406.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.148   0.239   1.382