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(134.93,134.37,132.98,130.1,128.24,127.52,126.94,127.38,130.95,128.65,127.37,127.04,125.95,124.06,121.55,119.82,119.19,118.77,118.31,119.47,119.79,117.46,115.74,114.97,112.83,111.44,110.6,109.67,107.96,107.56,116.12,114.38,113.96,113.95,114.99,113.64,112.53,110.59,110.1,109.38,110.43,114.67,114.48,114.76,113.27,111.56,109.89,108.04,107.53,106.11,104.11,103,104.74,104.14,101.98,100.91,100.02,98.49,97.38,95.86,93.99,94.09,93.44,93.61,98.31,103.97,104.12,107.63,105.22,104.59,101.54,99.47)
> 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/1iryw1476871307.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/2at4q1476871307.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/37y9t1476871307.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  0.940276716  0.875938664  0.815233597  0.761291865
 [6]  0.717811689  0.678139331  0.646483650  0.606772728  0.549487906
[11]  0.497766016  0.446133242  0.382504281  0.318590342  0.259351692
[16]  0.208928662  0.167235597  0.134243766  0.109275161  0.090672762
[21]  0.071839351  0.052795269  0.041501273  0.025829579  0.007037530
[26] -0.010747367 -0.024296227 -0.034670662 -0.033894853 -0.021596251
[31] -0.005080421 -0.009168776 -0.017322038 -0.028861222 -0.046655201
[36] -0.074940904 -0.106175787 -0.133270769 -0.155416139 -0.173729943
[41] -0.188046719 -0.201234503 -0.221782327 -0.256316363 -0.290590234
[46] -0.321553003 -0.350737356 -0.377017749 -0.399042720
> (mypacf <- c(rpacf$acf))
 [1]  0.940276716 -0.070604600 -0.001344000  0.022778159  0.056474247
 [6]  0.003498013  0.050531748 -0.085696361 -0.160160382  0.032097503
[11] -0.038147094 -0.161332792 -0.055756969 -0.017515354  0.002045668
[16]  0.040340578  0.050909373  0.018787730  0.069179233  0.040039724
[21] -0.004349439  0.065414988 -0.045009552 -0.058139994 -0.027447124
[26] -0.014165427 -0.046023647  0.066289292  0.069199321  0.010527410
[31] -0.145285999  0.013905195 -0.032659434 -0.058530906 -0.123144419
[36] -0.092425299 -0.053767965  0.013465546  0.009822928 -0.031860483
[41] -0.005908597 -0.007639078 -0.084447805  0.008299739 -0.002016355
[46] -0.035020193 -0.028928763 -0.025948399
> 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/421411476871307.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/5vsr91476871307.tab") 
> 
> try(system("convert tmp/1iryw1476871307.ps tmp/1iryw1476871307.png",intern=TRUE))
character(0)
> try(system("convert tmp/2at4q1476871307.ps tmp/2at4q1476871307.png",intern=TRUE))
character(0)
> try(system("convert tmp/37y9t1476871307.ps tmp/37y9t1476871307.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.155   0.085   1.260