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(96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,101.27,101.27,101.27,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,102.55,102.55,102.55,102.55,102.55,102.55,102.55,102.55,102.55,102.55,102.55,102.55,132.09,132.09,132.09)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '1'
> 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/15xw01457463830.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/2teoe1457463830.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/3qbgo1457463830.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 -0.019373011 -0.019695895 -0.002138863 -0.002421089
 [6] -0.002743972 -0.003066856 -0.003389739 -0.003712623 -0.001151104
[11] -0.002188122 -0.002511006 -0.031632262 -0.003144081 -0.003466964
[16] -0.003944295 -0.004360218 -0.004683102 -0.005005985 -0.005328869
[21] -0.005651752 -0.008259149 -0.007877626 -0.008200510  0.041637272
[26] -0.008858969 -0.009181852 -0.008865271 -0.009040738 -0.009363622
[31] -0.009686506 -0.010009389 -0.010332273 -0.009868275 -0.010191159
[36] -0.010514042 -0.100211684 -0.011172501 -0.011495385 -0.013313068
[41] -0.013721259 -0.014044142 -0.014367026 -0.014689909 -0.015012793
[46] -0.015583163 -0.015906047 -0.016228930  0.103914349
> (mypacf <- c(rpacf$acf))
 [1] -0.019373011 -0.020078744 -0.002919351 -0.002918941 -0.002952711
 [6] -0.003295198 -0.003646215 -0.004004650 -0.001478428 -0.002441094
[11] -0.002716300 -0.031915649 -0.004588923 -0.004980663 -0.004515990
[16] -0.004971199 -0.005338463 -0.005737008 -0.006128534 -0.006524560
[21] -0.009049006 -0.008886416 -0.009354551  0.039707692 -0.008187663
[26] -0.008552681 -0.010018125 -0.010281976 -0.010697536 -0.011083653
[31] -0.011493852 -0.011906571 -0.011938122 -0.012195080 -0.012607196
[36] -0.100123968 -0.017459744 -0.018080139 -0.017125229 -0.017811707
[41] -0.018414793 -0.019073343 -0.019734696 -0.020424507 -0.020647869
[46] -0.021665634 -0.022423581  0.092664898
> 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/48ih01457463830.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/5nu8c1457463830.tab") 
> 
> try(system("convert tmp/15xw01457463830.ps tmp/15xw01457463830.png",intern=TRUE))
character(0)
> try(system("convert tmp/2teoe1457463830.ps tmp/2teoe1457463830.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qbgo1457463830.ps tmp/3qbgo1457463830.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.178   0.215   1.401