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(193,223,254,284,294,304,314,314,314,314,324,335,335,335,345,365,365,385,385,385,395,395,405,405,416,416,426,436,446,446,466,476,476,476,476,486,497,507,517,527,527,547,547,557,557,557,567,567,598,598,618,628,638,669,679,689,689,689,689,709,719,729,790,831,942,952,962,1013,1033,1033,1043,1043,1053,1114,1155,1215,1236,1296,1317,1327,1347,1367,1367,1387,1408,1468,1479,1499,1499,1509,1519,1529,1539,1590,1620,1620,1651,1671,1691,1711,1721,1732,1732,1742,1762,1782,1813,1883,1904,1924,1934,1964,1985,1995,1995,2035,2066,2086,2157,2157)
> 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/1339r1470921335.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/2vo1l1470921335.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/3zff01470921335.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  0.235545590  0.262808427  0.150991624  0.038579673
 [6]  0.009567160 -0.041084294 -0.040316563  0.078170690  0.184980399
[11]  0.220190301  0.381632995  0.156218072  0.224588741  0.159205940
[16] -0.028770485  0.034404661 -0.060557419 -0.019480007  0.014285844
[21]  0.009185046  0.133699398  0.103326605  0.071449023 -0.006194241
[26] -0.010569447  0.005602842 -0.056430824 -0.131844931  0.016607428
[31]  0.024241173  0.033110870  0.101983746  0.059919345  0.075494448
[36] -0.062078418 -0.087624395 -0.027140461 -0.074056747 -0.097808108
[41] -0.010039069 -0.061973964 -0.014721684  0.121391334  0.016447679
[46]  0.069779643 -0.127958029 -0.022636802 -0.036260859
> (mypacf <- c(rpacf$acf))
 [1]  0.235545590  0.219505231  0.056698968 -0.062049063 -0.037852742
 [6] -0.044148356 -0.014899260  0.127731234  0.201082325  0.144789920
[11]  0.266318258 -0.057450423  0.039696433  0.053972158 -0.112160504
[16]  0.036912619 -0.023299651  0.001755783 -0.029435090 -0.090596526
[21]  0.047286434 -0.073426360 -0.041135542 -0.153242076 -0.071401861
[26]  0.095236545 -0.072305665 -0.084247431  0.107379518  0.052392071
[31]  0.037395426  0.035119552  0.081587793  0.066107587 -0.111707691
[36] -0.046611539  0.075944850  0.077805181 -0.065373001 -0.048543213
[41] -0.040672533 -0.103776278  0.052971520 -0.019234005  0.050320726
[46] -0.161214971 -0.031565265  0.018037829
> 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/432by1470921335.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/5c8xl1470921335.tab") 
> 
> try(system("convert tmp/1339r1470921335.ps tmp/1339r1470921335.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vo1l1470921335.ps tmp/2vo1l1470921335.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zff01470921335.ps tmp/3zff01470921335.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.189   0.119   1.328