R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(89.65,90.65,89.34,89.15,88.82,88.82,91.97,93.01,93.24,93.2,93.19,92.2,93.39,94.75,94.25,94.37,94.02,92.77,92.64,93.19,92.74,92.52,92.25,91.6,93.73,96.21,96.36,95.69,95.07,95.5,95.22,97.41,98.31,98.54,98.45,98.03,101.45,102.44,102.42,100.98,100.69,100.28,98.06,97.37,97.25,98.93,100.04,100.09,100.79,99.76,99.63,99.26,99.69,99.17,98.79,97.97,98.1,97.91,97.16,96.8,97.46,96.59,96.35,96.12,96.16,95.95,96.06,95.89,95.9,95.82,95.54,95.51)
> 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/1lh771457982329.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/2f9lw1457982329.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/33zh91457982329.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  0.931993127  0.853553151  0.771426891  0.701967788
 [6]  0.642918086  0.580600595  0.537163657  0.491635828  0.458117069
[11]  0.424206459  0.400731367  0.369200457  0.317275369  0.277418667
[16]  0.239349669  0.206877210  0.172189521  0.136772332  0.099863463
[21]  0.057453772  0.009984504 -0.042697761 -0.088850168 -0.145178883
[26] -0.195421009 -0.229436981 -0.263355449 -0.298876738 -0.339743706
[31] -0.367718700 -0.402885035 -0.423724757 -0.437496316 -0.444535462
[36] -0.439518662 -0.439381682 -0.404530825 -0.357352545 -0.312512353
[41] -0.287921620 -0.274340607 -0.264339654 -0.270752800 -0.273799106
[46] -0.278736104 -0.269037037 -0.248284767 -0.230925730
> (mypacf <- c(rpacf$acf))
 [1]  0.931993127 -0.114606702 -0.065064041  0.055213600  0.026202230
 [6] -0.078457250  0.116248681 -0.055142198  0.053911211 -0.021247639
[11]  0.068058941 -0.100716486 -0.146292640  0.091910099 -0.004213247
[16] -0.044705369 -0.012976642 -0.027770756 -0.072403232 -0.052455717
[21] -0.085447978 -0.074012805 -0.020151534 -0.111256480 -0.003739895
[26]  0.042437319 -0.093107825 -0.090510314 -0.057439881  0.031261956
[31] -0.138922400  0.079414413  0.026104785 -0.026891807  0.039858647
[36]  0.009865247  0.205549521  0.091255185 -0.004489879 -0.067159488
[41]  0.001522344 -0.032695119 -0.083956651 -0.016494524  0.005486391
[46]  0.033572615  0.083579938 -0.052325753
> 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/4l4jb1457982329.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/5jp2v1457982329.tab") 
> 
> try(system("convert tmp/1lh771457982329.ps tmp/1lh771457982329.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f9lw1457982329.ps tmp/2f9lw1457982329.png",intern=TRUE))
character(0)
> try(system("convert tmp/33zh91457982329.ps tmp/33zh91457982329.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.276   0.242   1.524