R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
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> x <- c(83.61,83.89,83.4,82.96,82.76,83.35,87.78,88.99,88.92,88.91,89.79,90.54,93.15,92.79,93.21,95.35,100.91,103.69,104.04,104.16,104.71,105.18,104.92,104.83,104.9,105.05,104.6,103.21,102.52,101.09,101.19,102.34,102.62,102.47,101.82,101.86,101.54,101.98,101.23,100.4,99.94,99.94,100,98.8,99.07,99.46,99.18,98.47,97.12,96.91,96.09,97.17,96.8,97.13,99.9,100.56,100.84,99.81,100.44,100.07,101.32,103.98,104.81,106.23,106.48,107.59,107.16,107.54,107.1,106.38,106.64,106.13)
> 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/1x0cq1489652487.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/29otf1489652487.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/30xsy1489652487.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  0.938734361  0.862413198  0.778073054  0.688005597
 [6]  0.589438965  0.486385987  0.398402098  0.315325211  0.232816725
[11]  0.145446677  0.055646346 -0.026373459 -0.090056010 -0.150916993
[16] -0.208342151 -0.256191883 -0.277026095 -0.279308964 -0.270881882
[21] -0.261720992 -0.249634511 -0.231764488 -0.211428358 -0.188540580
[26] -0.166353591 -0.145317664 -0.124883372 -0.104801197 -0.085008161
[31] -0.074092926 -0.063400857 -0.043977653 -0.018941795  0.007521105
[36]  0.032027999  0.057670054  0.083097363  0.110225957  0.128705959
[41]  0.138551720  0.146429256  0.158353877  0.169677232  0.170515679
[46]  0.165653547  0.152487690  0.132062403  0.104178776
> (mypacf <- c(rpacf$acf))
 [1]  0.938734361 -0.158354527 -0.095433892 -0.084048756 -0.116355752
 [6] -0.085617219  0.077036116 -0.039153960 -0.071720095 -0.118662853
[11] -0.109188736 -0.020034171  0.094301068 -0.066707054 -0.062314837
[16] -0.028756302  0.123884616  0.074066544  0.052659865 -0.077392133
[21] -0.067112644 -0.023018457  0.026201189  0.049417910 -0.001512950
[26] -0.089125407 -0.074458752 -0.006309783  0.067283292 -0.039137860
[31] -0.006259378  0.039985993  0.064225897  0.073973683  0.047920164
[36]  0.001420945 -0.025051163  0.033167398 -0.021967395 -0.008231466
[41]  0.013574783  0.017610356 -0.005282821 -0.052186186 -0.020633710
[46] -0.082700605 -0.056067047 -0.009886391
> 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/4bb3y1489652487.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/5r69e1489652487.tab") 
> 
> try(system("convert tmp/1x0cq1489652487.ps tmp/1x0cq1489652487.png",intern=TRUE))
character(0)
> try(system("convert tmp/29otf1489652487.ps tmp/29otf1489652487.png",intern=TRUE))
character(0)
> try(system("convert tmp/30xsy1489652487.ps tmp/30xsy1489652487.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.355   0.079   1.463