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(92.44,94.36,93.42,92.97,94.83,91.47,88.42,86.36,86.01,87.87,89.81,88.41,86.33,89.64,89.53,88.3,99.49,98.81,90.97,92.58,92.98,95,92.47,88.65,84.81,88.6,89.31,92.34,91.53,96.95,95.44,89.59,89.86,91.66,92.7,90.54,86.17,89.15,89.73,91.07,93.36,96.27,95,94.72,97.16,100.92,98.66,95.87,94.6,98.41,98.05,99.82,106.96,107.45,100.25,99.28,101.38,101,97.43,95.38,95.17,94.13,96.43,105.38,98.39,99.8,94.43,90.16,85.49,90.57,88.22,89.66)
> 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/114if1445625764.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/28n691445625764.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/3sei91445625764.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  0.762002042  0.546297017  0.445991270  0.361256604
 [6]  0.268029063  0.261614567  0.234914993  0.201332223  0.177663013
[11]  0.207332294  0.248539585  0.253378388  0.151023550 -0.008542851
[16] -0.103605066 -0.107523869 -0.113431942 -0.101919025 -0.120679877
[21] -0.139934309 -0.164567490 -0.126154406 -0.061538368 -0.031050689
[26] -0.077287947 -0.129290975 -0.153694143 -0.108595128 -0.099392702
[31] -0.085392839 -0.081843243 -0.089217573 -0.084866904 -0.079580656
[36] -0.044519603 -0.019360286 -0.123448789 -0.219354176 -0.241720528
[41] -0.216708800 -0.219680811 -0.178924377 -0.159931895 -0.162155112
[46] -0.183266891 -0.128769287 -0.101830994 -0.118225535
> (mypacf <- c(rpacf$acf))
 [1]  0.762002042 -0.081912146  0.139316318 -0.024929801 -0.033624763
 [6]  0.155032350 -0.059471544  0.040774799 -0.001503868  0.119153234
[11]  0.097203933 -0.015900376 -0.208531575 -0.237303855 -0.025470268
[16]  0.083446967 -0.009910270  0.017431762 -0.133379277  0.006364830
[21] -0.046484765  0.079054498  0.066684649 -0.003030320 -0.032438820
[26] -0.010823871  0.017051166  0.078160852 -0.128535374  0.019641777
[31] -0.017048087  0.029785996  0.048827685 -0.164398884  0.030543005
[36] -0.042189066 -0.205905258 -0.025414017 -0.075612524  0.054946038
[41] -0.077558701  0.082228120 -0.025246012 -0.036231701 -0.025269779
[46]  0.060520174  0.007534492 -0.046138577
> 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/4vb6b1445625764.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/5f49s1445625764.tab") 
> 
> try(system("convert tmp/114if1445625764.ps tmp/114if1445625764.png",intern=TRUE))
character(0)
> try(system("convert tmp/28n691445625764.ps tmp/28n691445625764.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sei91445625764.ps tmp/3sei91445625764.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.212   0.222   1.437