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(92.81,92.82,92.82,92.88,93.38,93.89,94.1,94.18,94.3,94.31,94.36,94.38,94.38,94.5,94.57,94.89,96.71,97.57,97.88,97.97,98.4,98.51,98.46,98.46,98.48,98.6,98.6,98.71,99.13,99.2,99.3,100.18,101.37,101.77,102.28,102.38,102.35,103.23,105.37,106.62,107,107.24,107.31,107.35,107.42,107.58,107.64,107.64,107.68,108.51,110.37,111.31,111.57,111.66,111.69,111.9,111.95,112.04,112.13,112.14,112.13,113.59,115.03,115.7,116.1,116.12,116.32,116.51,116.63,116.92,116.96,117.15)
> 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/12tta1495151348.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/298e51495151348.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/38df91495151348.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]  1.00000000  0.96453287  0.92588219  0.88554978  0.84501226  0.80487483
 [7]  0.76528685  0.72529532  0.68413556  0.64341230  0.60374525  0.56686745
[13]  0.53154203  0.49303217  0.45277900  0.41172672  0.37055772  0.33262740
[19]  0.29601816  0.25863293  0.22042522  0.18298498  0.14704806  0.11425407
[25]  0.08162390  0.04735348  0.01221557 -0.02350855 -0.05924802 -0.09457031
[31] -0.13075684 -0.16786240 -0.20317315 -0.23549724 -0.26479203 -0.28838564
[37] -0.31024238 -0.33280005 -0.35330365 -0.36736150 -0.37744334 -0.38335160
[43] -0.38645790 -0.38942887 -0.39243612 -0.39470150 -0.39752631 -0.40139839
[49] -0.40558161
> (mypacf <- c(rpacf$acf))
 [1]  0.964532866 -0.063744101 -0.042324265 -0.022392266 -0.015531343
 [6] -0.014727728 -0.029165312 -0.039924506 -0.016474164 -0.009215965
[11]  0.014166649 -0.005358831 -0.073027284 -0.048010309 -0.034552556
[16] -0.028154172  0.016962034 -0.015204893 -0.043321948 -0.039098804
[21] -0.015977418 -0.008461443  0.008546786 -0.038189249 -0.057018416
[26] -0.040817033 -0.035524068 -0.031868518 -0.037149501 -0.059061022
[31] -0.054202266 -0.011406376  0.005033283 -0.001479822  0.029305966
[36] -0.025674851 -0.050653145 -0.003718193  0.062497847  0.018837317
[41]  0.017383669  0.005800962 -0.019549491 -0.017389494 -0.008851765
[46] -0.040426679 -0.058104909 -0.037054594
> 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/452xn1495151348.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/5bbfe1495151348.tab") 
> 
> try(system("convert tmp/12tta1495151348.ps tmp/12tta1495151348.png",intern=TRUE))
character(0)
> try(system("convert tmp/298e51495151348.ps tmp/298e51495151348.png",intern=TRUE))
character(0)
> try(system("convert tmp/38df91495151348.ps tmp/38df91495151348.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.635   0.145   1.802