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(78.46,78.59,81.37,83.61,84.65,84.56,83.85,84.08,85.41,85.75,86.38,88.87,90.37,92.21,95.75,97.29,98.29,99.51,99.04,98.9,100.74,100.3,101.68,101.3,103.13,104.17,105.98,106.25,104.01,101.68,101.93,104.41,105.51,104.71,103.14,102.66,102.68,101.89,101.37,101.16,99.34,99.35,99.88,99.31,99.91,98.39,98.02,98.7,98.01,98.42,98.2,93.5,93.17,93.42,93.13,92.31,92.09,92.62,91.43,89.38)
> 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/139h31445675963.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/2jgqs1445675963.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/3cnjb1445675963.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  0.367050712  0.082790245  0.095436445  0.081010882
 [6]  0.239278124  0.275338956  0.132061174  0.187176060  0.101482471
[11]  0.192805278  0.354322806  0.208221655  0.077468603 -0.009864934
[16] -0.028616807  0.041822631  0.112212036  0.078489618 -0.042655824
[21] -0.129219783 -0.041685441  0.176656315  0.071700064 -0.038712423
[26] -0.177957034 -0.247024842 -0.151951065 -0.034568178 -0.051553538
[31]  0.035259541 -0.144074946 -0.127164641 -0.053486960 -0.147519742
[36] -0.131407101 -0.113517664 -0.230336417 -0.157257115 -0.100518599
[41] -0.116551982 -0.089059168 -0.086809646 -0.140747402 -0.100462782
[46] -0.056043225 -0.051196947 -0.098537487 -0.148915690
> (mypacf <- c(rpacf$acf))
 [1]  0.367050712 -0.060022599  0.098886443  0.017769306  0.237299834
 [6]  0.124222270 -0.005553437  0.156228579 -0.047089785  0.179055126
[11]  0.196098641 -0.002380848 -0.040545134 -0.122894841 -0.057324853
[16] -0.120868753  0.002459519 -0.049249843 -0.168767003 -0.126557971
[21] -0.044204990  0.182386534 -0.092484912  0.036765983 -0.123671866
[26] -0.100613564 -0.043612458 -0.011597565  0.003500189  0.157314539
[31] -0.044185054  0.069717111 -0.063300435 -0.096758987 -0.030119883
[36]  0.051609160 -0.037150786 -0.015777912 -0.034253538 -0.122328422
[41] -0.058223045  0.111650561 -0.040196201  0.008056078  0.063303348
[46]  0.018951824 -0.037513218  0.008346898
> 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/4mpm51445675963.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/548cp1445675963.tab") 
> 
> try(system("convert tmp/139h31445675963.ps tmp/139h31445675963.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jgqs1445675963.ps tmp/2jgqs1445675963.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cnjb1445675963.ps tmp/3cnjb1445675963.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.112   0.172   1.293