R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(77.34,78.15,78.31,78.71,78.68,78.85,78.97,79.47,80.6,82.24,83.25,84.55,85.91,86.84,87.44,87.79,88.08,88.38,88.53,88.79,88.85,89.26,89.31,89.39,89.76,89.94,89.99,90.08,89.95,90.2,89.7,89.5,89.25,89.13,89.07,89.06,89.15,89.38,89.4,89.51,89.62,89.65,89.68,89.92,90.26,90.89,91.08,91.13,91.83,92.66,93.45,93.95,94.12,94.31,94.25,94.51,94.58,94.85,95.31,95.75,96.06,96.4,96.57,96.47,96.34,96.22,96.2,96.71,97.05,97.82,98.22,98.5,98.94,99.5,99.89,100,100.1,100.16,100.05,100.03,100,100.32,100.53,100.49,100.38,100.22,100.5,100.57,100.6,100.23,100.29,100.01,100.13,100.22,100.2,100.34,100.73,100.29,101.11,101.09,101.01,101.27,101.57,101.69,101,101.43,101.13,101.23)
> 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/1112i1476876583.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/20inh1476876583.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/3gpbs1476876583.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  0.551610382  0.524818018  0.356988222  0.253963694
 [6]  0.149040199  0.077378399  0.088424691  0.070228999  0.066379810
[11]  0.093978370  0.051875397  0.091290907  0.018758991 -0.049609701
[16] -0.070934396 -0.119888884 -0.150957981 -0.210067830 -0.176159658
[21] -0.180434966 -0.161806389 -0.162426204 -0.115466941 -0.023608237
[26] -0.064146899 -0.036591291 -0.101185612 -0.065693420 -0.073790285
[31] -0.127478388 -0.067967805 -0.041753216 -0.022800407 -0.011227371
[36] -0.012204076  0.087311196  0.071652323  0.080501188  0.028109004
[41]  0.065946179  0.046306254  0.004143778 -0.006214565 -0.037261932
[46] -0.029612088 -0.010793759  0.057275721  0.104881491
> (mypacf <- c(rpacf$acf))
 [1]  0.551610382  0.316998371 -0.024922702 -0.065393854 -0.058480659
 [6] -0.032179308  0.089692592  0.044300503 -0.003691109  0.046005361
[11] -0.051652423  0.047428575 -0.063093620 -0.135737685 -0.017886118
[16] -0.027412289 -0.052958163 -0.094796294  0.004597400 -0.011406236
[21] -0.004936755 -0.053051997  0.028116084  0.141056839 -0.064702266
[26] -0.024955061 -0.108250864  0.030588517  0.054993608 -0.086639068
[31]  0.020916393  0.053693232 -0.012545935 -0.026691520 -0.045011450
[36]  0.093904265  0.060932948 -0.028543243 -0.111083225  0.058639211
[41]  0.026741163 -0.022822735 -0.063028489 -0.090002099  0.030505480
[46]  0.095652901  0.105129200  0.003324737
> 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/4ykhf1476876583.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/58rrs1476876583.tab") 
> 
> try(system("convert tmp/1112i1476876583.ps tmp/1112i1476876583.png",intern=TRUE))
character(0)
> try(system("convert tmp/20inh1476876583.ps tmp/20inh1476876583.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gpbs1476876583.ps tmp/3gpbs1476876583.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.222   0.096   1.334