R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(173019,173690,172439,171914,171968,169500,173898,172308,171568,164939,161275,160770,162466,160185,154836,154103,150495,142707,149962,149967,144572,143819,141070,144119,145330,143279,139063,139202,133632,134476,141859,140693,138047,138346,140167,146796,152228,155410,159032,160312,157687,160141,167421,167628,164403,163405,163229,171154,173323,172381,168983,165380,161641,161933,172018,168455,164332,161193,157645,161694,163411,161834,159511,156359,154223,151497,160607,159672,155601,154668,153960,157307,165218,165616,162212,159787,157454,156485,165887,166836,163541,163973,164805,167521,174347,173374,172198,171055,168385,167281,177670,177280,174846,174476,174595,178392,185345,183293,181081,177795,173552,170734,179293,178659,175894,174815,173506,175376)
> 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/1furm1451738921.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/2z0x41451738921.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/3e1lo1451738921.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  0.127806202 -0.241028676 -0.149826398 -0.182874566
 [6]  0.178891455  0.517312603  0.167843223 -0.168493610 -0.215976906
[11] -0.302971206  0.089010009  0.695528430  0.021180060 -0.304465360
[16] -0.210331160 -0.258087499  0.105372207  0.356639355  0.078015443
[21] -0.235309985 -0.314760523 -0.329058065  0.044219108  0.516297753
[26]  0.009836381 -0.292923918 -0.245698552 -0.246329999  0.073512710
[31]  0.290179469  0.116338462 -0.170280903 -0.214913633 -0.193672468
[36]  0.076296365  0.476202852  0.065559566 -0.213059961 -0.124030818
[41] -0.133308578  0.128295545  0.274700409  0.170442293 -0.122468483
[46] -0.141156469 -0.115340019  0.039419224  0.433299294
> (mypacf <- c(rpacf$acf))
 [1]  0.127806202 -0.261636787 -0.084601542 -0.231919317  0.199799555
 [6]  0.420829737  0.173258284  0.014601356 -0.057025298 -0.302785855
[11] -0.104478563  0.517390926 -0.224682437 -0.188773987 -0.063958397
[16] -0.021128086 -0.016214405 -0.182076459 -0.022557658 -0.095942561
[21] -0.101268388 -0.046893048 -0.093284999  0.043056607  0.053252309
[26]  0.011798195 -0.071177500  0.002837787 -0.053954310 -0.091433487
[31]  0.012523169  0.012708966  0.186244787  0.121700183 -0.016192845
[36]  0.058227353 -0.052121305 -0.040016880  0.017208007 -0.048463472
[41]  0.015996780 -0.104127255  0.070208960 -0.023635696  0.026336123
[46]  0.010123633 -0.129991146  0.063032123
> 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/40xkv1451738921.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/5zsam1451738921.tab") 
> 
> try(system("convert tmp/1furm1451738921.ps tmp/1furm1451738921.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z0x41451738921.ps tmp/2z0x41451738921.png",intern=TRUE))
character(0)
> try(system("convert tmp/3e1lo1451738921.ps tmp/3e1lo1451738921.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.162   0.215   1.384