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(84.71,85.17,84.93,85.1,85.19,85.38,85.95,86.04,85.68,85.79,85.79,86.05,86.14,86.82,86.93,87.03,87.13,87.09,87.65,87.6,87.03,87.12,87.08,87.56,87.31,87.89,88.2,87.7,88.19,88.65,89.48,89.65,89.34,89.73,89.77,90.26,90.03,91.09,90.94,91.03,91.14,91.51,91.99,91.91,91.8,91.8,91.44,91.83,91.46,92.17,91.91,92.06,92.33,92.73,93.35,93.28,93.22,93.31,93.21,93.14,93.82,94.18,94.44,94.35,94.38,94.72,95.25,95.16,94.9,95.09,95.22,95.39,96.57,97.05,97.11,97.08,97.5,97.92,98.44,98.44,98.06,98.2,98.19,98.36,98.41,98.97,99.45,98.95,99.7,100.12,100.62,100.75,100.47,100.71,100.85,101.03,101.13,101.38,101.73,101.89,102.02,102.11,102.77,102.49,102.52,102.69,102.32,102.6)
> 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. 1.2.291 ()
> #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/1e6oj1445592861.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/2yyzv1445592861.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/3pir71445592861.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 -0.152060695 -0.043563567 -0.147526373 -0.056103350
 [6]  0.139013847 -0.116563941  0.138724254 -0.102600322 -0.180122912
[11] -0.101605357 -0.046578420  0.532418782 -0.056866382 -0.072830225
[16] -0.264382696  0.071726503  0.069305779 -0.084370293  0.185117185
[21] -0.128238439 -0.140270611 -0.130098172  0.106680680  0.325018045
[26]  0.020025371 -0.073058734 -0.170944297 -0.014769685  0.044101912
[31] -0.019608557  0.044183867  0.002665935 -0.200320224 -0.087050936
[36]  0.065359024  0.280490426  0.042654497 -0.104792284  0.009570395
[41] -0.126441975  0.084992790  0.023750100  0.019712228  0.055675641
[46] -0.216240080 -0.027915773  0.079512271  0.241228136
> (mypacf <- c(rpacf$acf))
 [1] -0.152060695 -0.068264464 -0.169679049 -0.118340474  0.092395486
 [6] -0.122471845  0.098415481 -0.054917179 -0.228864263 -0.194941588
[11] -0.145348271  0.438586583  0.115658421 -0.049990766 -0.281791448
[16]  0.027047760 -0.031594669 -0.091306512  0.065352458 -0.017765026
[21] -0.081822048 -0.063778719  0.098663626  0.002063815  0.067146326
[26] -0.013266729  0.078415349 -0.143195260 -0.088216697 -0.056177080
[31] -0.118569415  0.103517557 -0.065183985  0.063609413 -0.175472721
[36]  0.077129667 -0.020571720  0.005672345  0.132229522 -0.095808463
[41]  0.028856783 -0.063754400  0.018219744 -0.021447457  0.048485597
[46] -0.038258504  0.198859487  0.023287989
> 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/4djc41445592861.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/583841445592861.tab") 
> 
> try(system("convert tmp/1e6oj1445592861.ps tmp/1e6oj1445592861.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yyzv1445592861.ps tmp/2yyzv1445592861.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pir71445592861.ps tmp/3pir71445592861.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.145   0.199   1.360