R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(8899,8899,9093,9093,9093,9116,9116,9116,10073,10073,10073,9223,9223,9223,9151,9151,9151,6727,6727,6727,7232,7232,7232,6370,6370,6370,6862,6862,6862,7029,7029,7029,7031,7031,7031,7223,7223,7223,8065,8065,8065,7657,7657,7657,7328,7328,7328,7115,7115,7115,7926,7926,7926,8681,8681,8681,8670,8670,8670,8028,8028)
> 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/11wcr1489690461.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/2dy7n1489690461.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/3h53o1489690461.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]  1.0000000000 -0.0011159811 -0.0005696794 -0.1821300619 -0.0006062690
 [6] -0.0006396869  0.2736985505 -0.0006762764 -0.0028521360 -0.4429653927
[11] -0.0028887255 -0.0028578701  0.1153046614 -0.0028944597 -0.0025535804
[16] -0.1411687366 -0.0025901700  0.0008610305  0.0807303872  0.0008244410
[21]  0.0006839010 -0.2151202723  0.0006473114  0.0006542219  0.1122486150
[26]  0.0006176323 -0.0002626802 -0.0099128902 -0.0002992697 -0.0005305484
[31]  0.1160881577 -0.0005671379 -0.0007984166 -0.1683540282 -0.0008350061
[36] -0.0017153186 -0.1163725743 -0.0017519081 -0.0017449977 -0.1173844747
[41] -0.0017815873 -0.0019221272  0.1389295950 -0.0019587168  0.0014924837
[46]  0.0670574721  0.0014558941  0.0017967734  0.0634057904
> (mypacf <- c(rpacf$acf))
 [1] -0.0011159811 -0.0005709256 -0.1821316214 -0.0010676929 -0.0009170911
 [6]  0.2487766874 -0.0003409469 -0.0029960458 -0.3971589291 -0.0051952662
[11] -0.0044322690 -0.0355081990 -0.0048083086 -0.0029728988  0.0741677230
[16] -0.0023559607 -0.0006245541 -0.1501271367 -0.0020462069 -0.0016037253
[21] -0.2287233038 -0.0041514792 -0.0036271532  0.1088038805 -0.0024474351
[26] -0.0014000764  0.0802207255 -0.0005874011 -0.0026121158 -0.1302376584
[31] -0.0041858187 -0.0038506955 -0.1659599879 -0.0062762037 -0.0040212217
[36] -0.1399958420 -0.0065036629 -0.0053522391 -0.1083340663 -0.0076329366
[41] -0.0095331527  0.0377224190 -0.0089201489 -0.0061252780  0.0296556081
[46] -0.0056480149 -0.0033899133 -0.0688360320
> 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/4w6mg1489690461.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/5tkuw1489690461.tab") 
> 
> try(system("convert tmp/11wcr1489690461.ps tmp/11wcr1489690461.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dy7n1489690461.ps tmp/2dy7n1489690461.png",intern=TRUE))
character(0)
> try(system("convert tmp/3h53o1489690461.ps tmp/3h53o1489690461.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.569   0.135   1.748