R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(369.82,373.1,374.55,375.01,374.81,375.31,375.31,375.39,375.59,376.26,377.18,377.26,377.26,381.87,387.09,387.14,388.78,389.16,389.16,389.42,389.49,388.97,388.97,389.09,389.09,391.76,390.96,391.76,392.8,393.06,393.06,393.26,393.87,394.47,394.57,394.57,394.57,399.57,406.13,407.03,409.46,409.9,409.9,410.14,410.54,410.69,410.79,410.97,410.97,413.8,423.31,423.85,426.6,426.26,426.26,426.32,427.14,427.55,428.29,428.8,428.8,434.87,435.66,440.75,440.99,441.04,441.04,441.88,441.92,442.48,442.81,442.81)
> 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/13u7o1366267541.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/2btw11366267541.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/3d42e1366267541.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  0.173665042  0.103424393 -0.096299487 -0.164723720
 [6] -0.163833731 -0.126166110 -0.192691374 -0.201930454 -0.051289749
[11] -0.098322852  0.267499751  0.364558411  0.327583258 -0.013995224
[16] -0.070477470 -0.183360602 -0.130874642 -0.108230381 -0.119097352
[21] -0.127841555 -0.067677517 -0.036992077  0.189812991  0.269357219
[26]  0.219316768  0.007323415 -0.043307863 -0.120895228 -0.123963000
[31] -0.107561043 -0.116951560 -0.121808434 -0.093663372 -0.053994849
[36] -0.026666393  0.303752810  0.140677180  0.041853829 -0.009347164
[41] -0.059510925 -0.065845402 -0.050472810 -0.066220324 -0.055929804
[46] -0.019808728 -0.090006944  0.095387106  0.113129361
> (mypacf <- c(rpacf$acf))
 [1]  0.173665042  0.075543195 -0.130687854 -0.143062285 -0.099497085
 [6] -0.071661948 -0.183866013 -0.207715269 -0.041412451 -0.168705750
[11]  0.199810471  0.266531600  0.186440401 -0.174791159 -0.096799710
[16] -0.076185701 -0.035090292 -0.022823204  0.035610063 -0.027585982
[21]  0.021715024 -0.079495715  0.090276737 -0.029555959  0.008703694
[26] -0.103736443  0.073715053  0.003461167 -0.018386902 -0.078832471
[31] -0.018856453 -0.103906429 -0.018540960 -0.120732986 -0.179680275
[36]  0.083866746  0.023221759 -0.109027432 -0.002048787 -0.043442787
[41] -0.010666625 -0.078363482  0.020369206  0.032482904  0.012766062
[46] -0.042055411  0.118853867 -0.079890440
> 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/49nj31366267542.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/542m51366267542.tab") 
> 
> try(system("convert tmp/13u7o1366267541.ps tmp/13u7o1366267541.png",intern=TRUE))
character(0)
> try(system("convert tmp/2btw11366267541.ps tmp/2btw11366267541.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d42e1366267541.ps tmp/3d42e1366267541.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.988   1.369   7.299