R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(78.46,78.59,81.37,83.61,84.65,84.56,83.85,84.08,85.41,85.75,86.38,88.87,90.37,92.21,95.75,97.29,98.29,99.51,99.04,98.9,100.74,100.3,101.68,101.3,103.13,104.17,105.98,106.25,104.01,101.68,101.93,104.41,105.51,104.71,103.14,102.66,102.68,101.89,101.37,101.16,99.34,99.35,99.88,99.31,99.91,98.39,98.02,98.7,98.01,98.42,98.2,93.5,93.17,93.42,93.13,92.31,92.09,92.62,91.43,89.38,86.21,86.65,88.62,87.3,88.33,88.67,88.23,88.85,90.38,89.65,89.2,87.87)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/10a931489659872.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/2xwlf1489659872.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/3guo71489659872.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  0.332380047  0.051549208  0.076237950  0.054095537
 [6]  0.212372186  0.254349862  0.085264090  0.141400251  0.171695065
[11]  0.163423370  0.289755654  0.258841633  0.029115595 -0.017286978
[16]  0.060542407 -0.006652767  0.052308876  0.106065424 -0.032930980
[21] -0.003124003 -0.022446496  0.123274216  0.093469193 -0.042475077
[26] -0.140804751 -0.132754762 -0.133215036 -0.082877067 -0.087888829
[31]  0.045155321 -0.029998120 -0.056535754 -0.065541859 -0.172512288
[36] -0.116396894 -0.093542008 -0.133240778 -0.143114265 -0.136125350
[41] -0.143102225 -0.056296506  0.026631293 -0.134712717 -0.099464742
[46] -0.085526849 -0.133826096 -0.121861882 -0.093717137
> (mypacf <- c(rpacf$acf))
 [1]  0.332380047 -0.066245903  0.090318424  0.001896245  0.222124022
 [6]  0.126968599 -0.033924283  0.137374439  0.080588194  0.080759369
[11]  0.189176006  0.115673084 -0.110880060 -0.077690892  0.020913791
[16] -0.169270915 -0.068648728  0.026416092 -0.134442494 -0.070782518
[21] -0.100827485  0.193980558 -0.101454430 -0.023149322 -0.027416124
[26] -0.063624560 -0.124027208 -0.029568390 -0.048094924  0.135615078
[31] -0.027142584  0.093911340 -0.065228409 -0.131764097  0.042904698
[36]  0.015690657 -0.027535768 -0.049697903  0.038061143 -0.122328613
[41] -0.006625219  0.105954437 -0.101549587  0.033011784  0.017115299
[46]  0.021066504 -0.106080095 -0.020597098
> 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/4k0gp1489659872.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/54nyo1489659872.tab") 
> 
> try(system("convert tmp/10a931489659872.ps tmp/10a931489659872.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xwlf1489659872.ps tmp/2xwlf1489659872.png",intern=TRUE))
character(0)
> try(system("convert tmp/3guo71489659872.ps tmp/3guo71489659872.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.186   0.085   1.292