R version 3.2.2 (2015-08-14) -- "Fire Safety"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(85.13,85.54,85.47,85.78,86.07,86.05,86.32,86.43,86.41,86.38,86.59,86.68,86.87,87.32,87.13,87.42,87.22,87.17,87.52,87.49,87.53,87.93,88.54,88.96,89.3,90.01,90.52,90.64,91.25,91.59,92.09,91.81,92.03,92.15,91.98,92.11,92.28,92.53,91.97,92.05,91.87,91.49,91.48,91.63,91.46,91.61,91.7,91.87,92.21,92.65,92.83,93.02,93.33,93.35,93.45,93.51,93.8,93.94,94.02,94.26,94.71,95.26,95.54,95.69,96.03,96.4,96.55,96.45,96.65,96.84,97.21,97.31,97.91,98.51,98.54,98.52,98.66,98.53,98.71,98.92,98.96,99.25,99.32,99.41,99.36,99.58,99.77,99.77,100.03,100.2,100.24,100.1,100.03,100.18,100.29,100.41,100.6,100.75,100.79,100.44,100.29,100.34,100.46,100.12,100.06,100.28,100.28,100.4)
> 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. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) 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)
> 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/13anv1445590509.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/2crvw1445590509.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/3dzyu1445590509.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  0.976346304  0.953046544  0.928315832  0.903728361
 [6]  0.878803997  0.852149309  0.825983135  0.799227083  0.771244034
[11]  0.741492105  0.711853446  0.682194565  0.652773570  0.624534353
[16]  0.595407024  0.566957677  0.537286586  0.506391991  0.476358753
[21]  0.446119624  0.416019973  0.386528977  0.358651062  0.332004748
[26]  0.305230454  0.280256470  0.256511082  0.233257234  0.211728634
[31]  0.191249452  0.172515442  0.152218631  0.132525603  0.112504106
[36]  0.091533854  0.071953224  0.053418397  0.035356662  0.015910752
[41] -0.003383913 -0.023305127 -0.045144648 -0.067175077 -0.088385709
[46] -0.109977424 -0.131257309 -0.152273281 -0.171959149
> (mypacf <- c(rpacf$acf))
 [1]  0.976346304 -0.004397219 -0.042485246 -0.010218778 -0.019189371
 [6] -0.050638226 -0.004121169 -0.024727635 -0.042305683 -0.053214228
[11] -0.012892612 -0.016631333 -0.012027771  0.009811755 -0.034230193
[16] -0.005932730 -0.041590770 -0.046087432 -0.001379449 -0.022020369
[21] -0.021293676 -0.006864443  0.013768794  0.005547996 -0.022577351
[26]  0.020618824  0.008597076 -0.014360224  0.017563411  0.002394274
[31]  0.012506212 -0.054408156 -0.010849008 -0.025455305 -0.045684524
[36]  0.006789443  0.006388738 -0.016201179 -0.051156686 -0.020364882
[41] -0.032514487 -0.065557666 -0.030505417 -0.001280158 -0.039947989
[46] -0.019984453 -0.017985219  0.007353327
> 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/4bjv21445590509.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/5t2581445590509.tab") 
> 
> try(system("convert tmp/13anv1445590509.ps tmp/13anv1445590509.png",intern=TRUE))
character(0)
> try(system("convert tmp/2crvw1445590509.ps tmp/2crvw1445590509.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dzyu1445590509.ps tmp/3dzyu1445590509.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.085   0.225   1.322