R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(75.6,74,75.3,83.1,84.9,83.5,88.2,87.4,77.8,74.5,75.3,78.7,71.4,75.8,79.2,84.4,84.4,87.2,92.4,88.5,94.8,100.9,110,107.9,111.2,116.7,125.8,131.5,146.2,155.4,157.5,137.2,121.3,89.1,69.6,56.7,58.5,56.4,60.5,64.6,73.2,84.6,80.4,88.4,84.6,90.8,94.9,93.1,96.6,93.1,98.3,105,95.6,94.3,95.3,97.1,98.1,104.4,107.8,114.3,118.7,124.1,134.2,142.4,133.8,131,133.2,125.9,126.2,122.7,126.6,124.8,128,134.1,138.8,134,124,110.4,116.7,124.7,126,122.8,120.2,121.2,125.4,127.9,122,117.5,117.9,117.9,122.7,125.7,126.1,123.2,120.6,123.5)
> 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/1qdzb1425582372.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/2sa7w1425582372.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/3wtq01425582372.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  0.943248327  0.842308994  0.714877084  0.588147109
 [6]  0.466553588  0.361280756  0.281870179  0.221423553  0.173420599
[11]  0.138236480  0.107727805  0.077312319  0.043814795  0.021493480
[16]  0.009591593  0.000551179 -0.005959018 -0.008530094 -0.005146632
[21] -0.012917953 -0.017836681 -0.027097796 -0.038146146 -0.057446298
[26] -0.069469798 -0.083442952 -0.080981984 -0.065861526 -0.030049807
[31]  0.017970687  0.073463065  0.122881465  0.157310577  0.161709718
[36]  0.145298976  0.117507536  0.091637963  0.065836884  0.044566741
[41]  0.033765108  0.027256461  0.027903502  0.019571897  0.007713790
[46] -0.025092984 -0.058448044 -0.085403674 -0.107803699
> (mypacf <- c(rpacf$acf))
 [1]  0.943248327 -0.429881200 -0.174501845  0.069338211 -0.049633234
 [6]  0.033331821  0.108612584 -0.049405503 -0.051518734  0.053958547
[11] -0.063121469 -0.055292875 -0.013835098  0.124325337  0.011288077
[16] -0.081281584  0.012502867  0.015210353  0.018283001 -0.144583319
[21]  0.126806978 -0.067204863 -0.045109233 -0.037027122  0.115417692
[26] -0.156547684  0.213407241  0.080753828  0.039699504  0.021304528
[31]  0.078754178 -0.075992373 -0.109421827 -0.126511498  0.067751219
[36]  0.051063229  0.029444123 -0.023895388  0.009436684 -0.015024403
[41] -0.022819834  0.087771945 -0.152553359 -0.027759940 -0.090552415
[46]  0.082828942  0.033109023 -0.130269072
> 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/40g6g1425582372.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/53cum1425582372.tab") 
> 
> try(system("convert tmp/1qdzb1425582372.ps tmp/1qdzb1425582372.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sa7w1425582372.ps tmp/2sa7w1425582372.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wtq01425582372.ps tmp/3wtq01425582372.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.252   0.226   1.483