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(1943,1932,1922,1901,2108,2098,1943,1839,1850,1850,1860,1881,1839,1819,1757,1664,1922,1839,1633,1674,1633,1736,1591,1684,1602,1581,1416,1354,1664,1602,1405,1529,1426,1509,1426,1571,1447,1426,1230,1168,1612,1509,1333,1498,1374,1333,1312,1416,1240,1240,1095,1044,1560,1426,1302,1405,1261,1199,1250,1405,1199,1281,1178,1137,1591,1498,1250,1374,1312,1354,1426,1622,1488,1540,1457,1395,1860,1746,1467,1426,1343,1374,1354,1529,1343,1405,1364,1323,1829,1726,1447,1343,1188,1199,1178,1323,1064,1054,1013,899,1467,1405,1095,1002,847,816,713,858,486,444,403,331,940,889,568,506,351,362,300,403)
> 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/18bwj1468831143.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/2v6321468831143.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/3tdmc1468831143.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  0.870130427  0.773248680  0.726387674  0.666672799
 [6]  0.654132025  0.623994233  0.589084972  0.534203808  0.491048772
[11]  0.439539272  0.430461189  0.460827955  0.345681194  0.258682590
[16]  0.225840680  0.182410003  0.173735493  0.155886944  0.137878763
[21]  0.094031290  0.065789535  0.030390246  0.037961457  0.080348081
[26]  0.001353566 -0.054810162 -0.061282339 -0.078711876 -0.070320385
[31] -0.066166032 -0.061412516 -0.079703531 -0.081297386 -0.094150873
[36] -0.073148884 -0.025066829 -0.077835875 -0.112450676 -0.100219893
[41] -0.094505283 -0.079246652 -0.066737092 -0.052136292 -0.056598523
[46] -0.044524017 -0.038898104 -0.008195934  0.047635919
> (mypacf <- c(rpacf$acf))
 [1]  0.870130427  0.066379208  0.167341417 -0.030522663  0.199606017
 [6] -0.042072307  0.040750429 -0.134823908  0.050450181 -0.126002360
[11]  0.194496291  0.122902057 -0.502329795  0.003119267  0.088256663
[16]  0.050621612 -0.052998636  0.018140796  0.037594985 -0.081481072
[21]  0.083617438 -0.039142434  0.097019600 -0.030427810 -0.157815073
[26] -0.010948881  0.048899799  0.017687893 -0.038949811  0.018763401
[31]  0.015761473  0.012344492  0.070574773 -0.030702616  0.018784834
[36] -0.045691388 -0.030627021 -0.025678257  0.044992900  0.023047218
[41] -0.054837627 -0.001256102  0.032082118  0.057129919  0.030295901
[46]  0.034355200  0.004767116  0.021256925
> 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/4xltj1468831143.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/56s3e1468831143.tab") 
> 
> try(system("convert tmp/18bwj1468831143.ps tmp/18bwj1468831143.png",intern=TRUE))
character(0)
> try(system("convert tmp/2v6321468831143.ps tmp/2v6321468831143.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tdmc1468831143.ps tmp/3tdmc1468831143.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.135   0.125   1.273