R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(93.55,94.11,94.47,94.38,94.42,94.39,94.42,94.34,94.59,94.63,94.84,94.98,95.19,95.76,96.08,96.04,96.2,96.31,96.3,96.29,96.46,96.66,96.83,97,97.1,97.33,97.31,97.16,97.4,97.4,97.52,97.77,98,98.2,98.48,98.53,98.71,99.03,99.52,99.65,99.98,99.94,100.12,100.17,100.38,100.75,100.84,100.91,100.9,101.15,101.4,101.39,101.55,101.73,101.7,101.65,101.73,101.53,101.58,101.58,101.71,101.71,101.98,101.99,101.95,102.11,102.28,102.32,102.18,102.14,102.29,102.33)
> 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. 1.2.327 (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/1hysc1489957495.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/2m7xo1489957495.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/3bslb1489957495.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  0.962659971  0.928249885  0.896214598  0.861182882
 [6]  0.823699342  0.784653008  0.745242892  0.704233082  0.663293439
[11]  0.620851346  0.580360249  0.539128247  0.498037443  0.460472499
[16]  0.424759604  0.385726396  0.347223188  0.307987088  0.267114048
[21]  0.226174229  0.185991332  0.145934185  0.107418703  0.070893107
[26]  0.033397352 -0.002881827 -0.039899805 -0.077198947 -0.112360449
[31] -0.148426439 -0.183554958 -0.217769410 -0.249239374 -0.278978681
[36] -0.303780338 -0.326723247 -0.348176372 -0.367650139 -0.381622130
[41] -0.394001194 -0.402443195 -0.410156780 -0.416031571 -0.421916304
[46] -0.424766660 -0.425601326 -0.425964504 -0.424346925
> (mypacf <- c(rpacf$acf))
 [1]  0.962659971  0.020954486  0.016084453 -0.055296754 -0.054374608
 [6] -0.047258769 -0.029625824 -0.044173559 -0.022521930 -0.044780230
[11]  0.001520817 -0.033447106 -0.021347119  0.020589935  0.004597992
[16] -0.066140465 -0.025253178 -0.047677889 -0.053994521 -0.037205665
[21] -0.023537253 -0.030592039 -0.009924266 -0.003036716 -0.040846105
[26] -0.021403994 -0.045738018 -0.042823483 -0.017598183 -0.054297108
[31] -0.029085435 -0.035330372 -0.005040438 -0.011035581  0.031687127
[36] -0.004952779 -0.009497020 -0.016826945  0.035720569 -0.012643872
[41]  0.021011549 -0.023573657 -0.006087901 -0.039500911  0.014348173
[46] -0.000206355 -0.012015608  0.001645283
> 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/4ghw11489957495.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/5b8jb1489957495.tab") 
> 
> try(system("convert tmp/1hysc1489957495.ps tmp/1hysc1489957495.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m7xo1489957495.ps tmp/2m7xo1489957495.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bslb1489957495.ps tmp/3bslb1489957495.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.299   0.096   1.415