R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(28886,28549,33348,29017,30924,30435,29431,30290,31286,30622,31742,30391,30740,32086,33947,31312,33239,32362,32170,32665,31412,34891,33919,30706,32846,31368,33130,31665,33139,32201,32230,30287,31918,33853,32232,31484,31902,30260,32823,32018,32100,31952,33274,29491,32751,33643,31226,30976,28880,29325,34923,32642,31487,33832,32724,29545,32338,32743,32231,32536)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> 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/12nq81476815580.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/25ie31476815580.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/30lzf1476815580.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 -0.47490507 -0.10463397  0.15766693 -0.11444825 -0.06305653
 [7]  0.22714508 -0.18117383  0.13131692  0.03190723 -0.21014730 -0.05493097
[13]  0.44831298 -0.37458504  0.19523554 -0.14238314 -0.02265607  0.10885095
[19] -0.03454063 -0.04495589  0.15787302 -0.12675951 -0.03597210 -0.03908289
[25]  0.16195416 -0.09851506  0.14208072 -0.27191982  0.17826923 -0.01467927
[31] -0.09281819  0.09045955  0.07111948 -0.13149996  0.05707726 -0.11527489
[37]  0.08693973  0.07134027 -0.04163801 -0.12267086  0.22233289 -0.20822361
[43]  0.05051599  0.11191597 -0.09674317  0.01571468  0.02850704 -0.13893260
[49]  0.14085129
> (mypacf <- c(rpacf$acf))
 [1] -0.474905071 -0.426318457 -0.182527798 -0.227897170 -0.332504413
 [6] -0.071269143 -0.173876885  0.057517848  0.184450756  0.017177889
[11] -0.308732673  0.262015383  0.069542248  0.305267227 -0.098364285
[16] -0.043467779  0.053283644 -0.018205658  0.044238050 -0.069352421
[21] -0.032929332  0.046011736 -0.073068990 -0.082374952 -0.058402518
[26]  0.047029151 -0.090723501 -0.046716614 -0.067854662 -0.095874952
[31] -0.085352680  0.009550296 -0.017915643 -0.007092880 -0.034274044
[36] -0.111877670  0.038164186 -0.104200911 -0.003608732  0.067732824
[41] -0.009305048  0.039774751  0.106977129  0.064548309  0.018659484
[46] -0.050741419  0.008576866 -0.019457032
> 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/41uv91476815580.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/53sg51476815580.tab") 
> 
> try(system("convert tmp/12nq81476815580.ps tmp/12nq81476815580.png",intern=TRUE))
character(0)
> try(system("convert tmp/25ie31476815580.ps tmp/25ie31476815580.png",intern=TRUE))
character(0)
> try(system("convert tmp/30lzf1476815580.ps tmp/30lzf1476815580.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.145   0.095   1.272