R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1795,1756,2237,1960,1829,2524,2077,2366,2185,2098,1836,1863,2044,2136,2931,3263,3328,3570,2313,1623,1316,1507,1419,1660,1790,1733,2086,1814,2241,1943,1773,2143,2087,1805,1913,2296,2500,2210,2526,2249,2024,2091,2045,1882,1831,1964,1763,1688,2149,1823,2094,2145,1791,1996,2097,1796,1963,2042,1746,2210,2949,3093,3718,3024,1522,1502,1373,1607,1768,1622,1447,1768)
> 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/1pdj71449153695.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/2v1gl1449153695.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/3201k1449153695.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  0.049304965 -0.050973543  0.003206661 -0.393394053
 [6] -0.168845634  0.019464723 -0.045099240 -0.099411008  0.162979494
[11]  0.015303576 -0.025033323  0.239198638 -0.165762697  0.032869946
[16]  0.045620858 -0.185387274 -0.031079422 -0.033131982  0.030492892
[21] -0.046791674  0.118584528  0.018988815 -0.007663118  0.121353683
[26] -0.005742591  0.011215190  0.015723436 -0.080715522 -0.059326071
[31] -0.045024650  0.098485064 -0.112998280  0.046634181  0.113762428
[36] -0.092322369  0.088611052  0.046646097 -0.120864751  0.041637769
[41] -0.036238614 -0.149500351 -0.134262403  0.020756181 -0.030689396
[46]  0.260615482  0.272813073 -0.038013116  0.053363256
> (mypacf <- c(rpacf$acf))
 [1]  0.049304965 -0.053534664  0.008539152 -0.398873532 -0.150027935
 [6] -0.026603072 -0.069118378 -0.308509392  0.026435051 -0.062286261
[11] -0.094649606  0.073259000 -0.203122905  0.089844292 -0.052591061
[16] -0.114160624 -0.115422589 -0.093258114  0.036473811 -0.193703216
[21] -0.072844953 -0.059404182 -0.018636724 -0.086418699  0.046703467
[26] -0.052245860  0.058940793 -0.052379918 -0.036681234 -0.014992418
[31]  0.132206647 -0.141776518 -0.047520859  0.124399788 -0.023567127
[36] -0.003079767  0.026600251 -0.018796551  0.126345046 -0.086428301
[41] -0.100278020 -0.226357235 -0.044062692 -0.073599461  0.085734568
[46]  0.007372597  0.060267801 -0.060951447
> 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/4lust1449153695.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/51k1c1449153695.tab") 
> 
> try(system("convert tmp/1pdj71449153695.ps tmp/1pdj71449153695.png",intern=TRUE))
character(0)
> try(system("convert tmp/2v1gl1449153695.ps tmp/2v1gl1449153695.png",intern=TRUE))
character(0)
> try(system("convert tmp/3201k1449153695.ps tmp/3201k1449153695.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.192   0.225   1.422