R version 3.2.2 (2015-08-14) -- "Fire Safety"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(250.71,251.57,260.85,265.47,262.37,272.39,277.49,274.41,274.42,267.1,258.84,253.97,253.88,253.3,249.86,246,248.42,250.29,246.9,255.2,253.33,251.02,254.5,253.18,256.03,262.15,259.94,253.75,247.69,242.42,231.82,235.88,240.68,260.15,265.32,265.02,279.86,298.3,304.14,295.26,281.93,280.46,272.06,270.05,271.84,268.49,270.92,273.22,269.43,271.21,265.4,265.53,276.78,281.49,283.75,281.45,282.1,274.01,275.51,277.62,275.33,271.15,270.89,265.29,266.96,266.87,267.68,272.37,285.05,296.79,309.15,304.19,307.33,290.68,292.26,294.81,293.67,293.57,286.28,278.93,284.22,282.09,282.26,285.79,294.01,292.73,303.01,298.67,292.38,295.7,294.9,299.46,299.75,294.76,297.68,300.24,302.48,310.2,311.49,307.37,304.58,305.87,309.81,313.91,313.2,307.85,306.89,310.83)
> 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/1m8hv1445682537.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/2ddz91445682537.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/3xf4h1445682537.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]  1.00000000  0.93514321  0.84872930  0.76088299  0.67363374  0.59707949
 [7]  0.53771920  0.49243588  0.47012596  0.45961359  0.45855190  0.45994741
[13]  0.46655885  0.47014093  0.48092534  0.48082225  0.46444183  0.43132144
[19]  0.38916952  0.33956764  0.29720203  0.24734446  0.19282115  0.15055387
[25]  0.11775511  0.11322290  0.12752171  0.15408253  0.18017053  0.20609664
[31]  0.23063861  0.23848261  0.22437857  0.19208469  0.15002695  0.10036334
[37]  0.03264762 -0.02496514 -0.07400480 -0.10503967 -0.13245860 -0.14081864
[43] -0.13215917 -0.11827484 -0.10737121 -0.09205510 -0.08264791 -0.07140076
[49] -0.06730998
> (mypacf <- c(rpacf$acf))
 [1]  0.935143205 -0.205275237 -0.031295182 -0.045976661  0.035414535
 [6]  0.067662861  0.037588764  0.128914912  0.029028960  0.060303385
[11]  0.012481597  0.072633298  0.006032473  0.114541038 -0.059396122
[16] -0.068034847 -0.083945310 -0.033525589 -0.042901335  0.039027415
[21] -0.119339406 -0.100791019  0.026910257 -0.035616895  0.186561371
[26]  0.033185224  0.088910370 -0.060627875  0.033966573  0.047591611
[31] -0.045508017 -0.061443217 -0.065174106 -0.029775670 -0.098343249
[36] -0.161157694  0.053865021 -0.014883106  0.049347981 -0.154436412
[41]  0.035894714  0.057231354 -0.033261661 -0.008279091  0.015402918
[46] -0.021846603  0.068346695  0.004142137
> 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/4pc4u1445682537.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/5tlhi1445682537.tab") 
> 
> try(system("convert tmp/1m8hv1445682537.ps tmp/1m8hv1445682537.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ddz91445682537.ps tmp/2ddz91445682537.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xf4h1445682537.ps tmp/3xf4h1445682537.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.092   0.219   1.309