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(29312,29336,29357,29380,29402,29426,29448,29471,29495,29517,29540,29563,29586,29609,29631,29654,29677,29700,29723,29746,29769,29792,29815,29837,29861,29884,29905,29928,29951,29974,29996,30020,30043,30065,30089,30111,30134,30158,30179,30202,30224,30248,30270,30293,30317,30339,30362,30385,30408,30431,30452,30476,30498,30521,30544,30567,30590,30613,30636,30659,30682,30705,30727,30750,30773,30796,30818,30842,30865,30887,30911,30933,30956,30980,31001,31024,31046,31070,31092,31115,31139,31161,31184,31207,31230,31253,31274,31298,31320,31343,31366,31389,31412,31435,31458,31481,31504,31527,31548,31571,31594,31617,31640,31663,31686,31709,31732,31754)
> 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/1keu51471088721.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/2rfcc1471088721.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/32jtz1471088721.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  0.972233049  0.944484279  0.916717237  0.888986193
 [6]  0.861278310  0.833648079  0.806060571  0.778547163  0.751140678
[11]  0.723805712  0.696528326  0.669363582  0.642320217  0.615408581
[16]  0.588615415  0.561972808  0.535490396  0.509177612  0.483044715
[21]  0.457100862  0.431333060  0.405796204  0.380432037  0.355272233
[26]  0.330371008  0.305716529  0.281272369  0.257070406  0.233165446
[31]  0.209544510  0.186172222  0.163148041  0.140414452  0.117980498
[36]  0.095855537  0.074071891  0.052638254  0.031565328  0.010839583
[41] -0.009529679 -0.029533103 -0.049093367 -0.068290588 -0.087070922
[46] -0.105401639 -0.123318105 -0.140811447 -0.157849123
> (mypacf <- c(rpacf$acf))
 [1]  0.97223305 -0.01374695 -0.01460413 -0.01382936 -0.01425668 -0.01346757
 [7] -0.01428664 -0.01392040 -0.01351267 -0.01434127 -0.01480183 -0.01401396
[13] -0.01404627 -0.01405029 -0.01448538 -0.01410344 -0.01411565 -0.01413401
[19] -0.01413414 -0.01415209 -0.01457462 -0.01376768 -0.01500194 -0.01463224
[25] -0.01382927 -0.01420967 -0.01505055 -0.01467028 -0.01384805 -0.01423537
[31] -0.01505035 -0.01341610 -0.01459086 -0.01459606 -0.01458836 -0.01415561
[37] -0.01412868 -0.01407053 -0.01444831 -0.01441475 -0.01437665 -0.01308533
[43] -0.01462382 -0.01376793 -0.01325022 -0.01396557 -0.01389035 -0.01337472
> 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/4r64w1471088721.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/52y5x1471088721.tab") 
> 
> try(system("convert tmp/1keu51471088721.ps tmp/1keu51471088721.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rfcc1471088721.ps tmp/2rfcc1471088721.png",intern=TRUE))
character(0)
> try(system("convert tmp/32jtz1471088721.ps tmp/32jtz1471088721.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.182   0.142   1.341