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(26.133,25.979,25.541,25.308,25.663,25.78,25.328,24.806,24.651,24.531,24.633,25.174,24.449,24.277,24.393,24.301,24.381,24.286,24.335,24.273,24.556,24.841,25.464,25.514,25.531,25.042,24.676,24.809,25.313,25.64,25.447,25.021,24.752,24.939,25.365,25.214,25.563,25.475,25.659,25.841,25.888,25.759,25.944,25.818,25.789,25.662,26.927,27.521,27.485,27.444,27.395,27.45,27.437,27.45,27.458,27.816,27.599,27.588,27.667,27.64)
> 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/1l9hk1445596596.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/2uj3p1445596596.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/3w6dm1445596596.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  0.93134516  0.84570488  0.77760514  0.73161565  0.68399836
 [7]  0.63557645  0.56990418  0.49754490  0.42790257  0.36583355  0.30431259
[13]  0.23394706  0.15595618  0.08465019  0.05201198  0.03686921  0.03180436
[19]  0.01564618 -0.02052949 -0.07243835 -0.11397965 -0.12574135 -0.12578380
[25] -0.13600312 -0.15449064 -0.18995081 -0.21249506 -0.22207288 -0.24099305
[31] -0.27500255 -0.31185585 -0.33749222 -0.34594933 -0.35076602 -0.35252443
[37] -0.37029785 -0.39412964 -0.41499036 -0.41782953 -0.40366544 -0.36935985
[43] -0.33510361 -0.30807219 -0.27983035 -0.24474530 -0.20342406 -0.16358552
[49] -0.13278525
> (mypacf <- c(rpacf$acf))
 [1]  0.931345159 -0.163646641  0.104446670  0.097463834 -0.063482118
 [6]  0.007562597 -0.154905979 -0.064390848 -0.038391443 -0.037283622
[11] -0.050367076 -0.113309633 -0.083518499 -0.009237430  0.216400561
[16]  0.036051278  0.116164459 -0.026628300 -0.140215784 -0.131633609
[21] -0.071731219  0.102626552 -0.008656046 -0.052743474 -0.020108392
[26] -0.205844690  0.058905437 -0.010041060 -0.074809336 -0.025924655
[31] -0.009980874  0.032930993 -0.014766097 -0.113883162  0.017051186
[36] -0.082483957  0.009279237 -0.002720271  0.037721407 -0.015058524
[41]  0.154751445  0.018230990 -0.003114019  0.059044158 -0.023889163
[46]  0.044454175 -0.045859007 -0.048806633
> 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/49xwg1445596596.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/5l0471445596596.tab") 
> 
> try(system("convert tmp/1l9hk1445596596.ps tmp/1l9hk1445596596.png",intern=TRUE))
character(0)
> try(system("convert tmp/2uj3p1445596596.ps tmp/2uj3p1445596596.png",intern=TRUE))
character(0)
> try(system("convert tmp/3w6dm1445596596.ps tmp/3w6dm1445596596.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.095   0.252   1.360