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(0.69867,0.68968,0.69233,0.68293,0.68399,0.66895,0.68756,0.68527,0.6776,0.68137,0.67933,0.67922,0.68598,0.68297,0.68935,0.69463,0.6833,0.68666,0.68782,0.67669,0.67511,0.67254,0.67397,0.67286,0.66341,0.668,0.68021,0.67934,0.68136,0.67562,0.6744,0.67766,0.68887,0.69614,0.70896,0.72064,0.74725,0.75094,0.77494,0.79487,0.79209,0.79152,0.79308,0.79279,0.79924,0.78668,0.83063,0.90448,0.91819,0.88691,0.91966,0.89756,0.88445,0.8567,0.86092,0.86265,0.89135,0.91557,0.89892,0.89972,0.88305,0.87604,0.9016,0.87456,0.85714,0.82771,0.83566,0.82363,0.83987,0.87638,0.8551,0.84813,0.84712,0.84635,0.86653,0.88291,0.87788,0.88745,0.88476,0.87668,0.87172,0.87036,0.8574,0.84405,0.8321,0.83696,0.83448,0.82188,0.80371,0.80579,0.78827,0.78884,0.79821,0.80665,0.80389,0.81237,0.83271,0.8625,0.85996,0.85076,0.84914,0.85191,0.86192,0.85904,0.84171,0.8472,0.8378,0.83639,0.82674,0.8251,0.8317,0.8252,0.81535,0.80409,0.7931,0.7973,0.79113,0.78861,0.79054,0.7883)
> 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/1b6n61425578083.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/2gh1n1425578083.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/30wj31425578083.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  0.976274892  0.945692115  0.915678881  0.883477401
 [6]  0.852077358  0.820247707  0.791065986  0.762020801  0.730404186
[11]  0.696844787  0.660505741  0.623195930  0.580356953  0.540526657
[16]  0.504100081  0.470204022  0.436922753  0.411016882  0.384876883
[21]  0.356437347  0.327967842  0.295655614  0.259344370  0.221913611
[26]  0.182585914  0.144420225  0.110866077  0.076387031  0.040590498
[31]  0.003804806 -0.035773167 -0.072567740 -0.104212427 -0.134258627
[36] -0.161264801 -0.187762328 -0.210963800 -0.230747074 -0.245903918
[41] -0.258903989 -0.271445403 -0.286527595 -0.299180637 -0.308960049
[46] -0.314968651 -0.320549588 -0.321351427 -0.312067156
> (mypacf <- c(rpacf$acf))
 [1]  0.976274892 -0.158263397  0.017816562 -0.070285939  0.015988128
 [6] -0.036653980  0.049151970 -0.035571316 -0.064598624 -0.053551938
[11] -0.069183476 -0.026707362 -0.141810308  0.080334015  0.007996361
[16]  0.034360676 -0.043037988  0.157887600 -0.096018629 -0.027939152
[21] -0.017499864 -0.093563362 -0.100659937 -0.035979872 -0.061464167
[26] -0.045938439  0.067393299 -0.108013296 -0.025031683 -0.103492268
[31] -0.030833827  0.050815588  0.102616468 -0.021932903  0.071205041
[36] -0.082346023  0.027970946  0.024963273  0.044237992 -0.009828284
[41] -0.007579278 -0.122307364  0.036318045  0.035304762  0.013142670
[46] -0.017783614  0.092883159  0.178081295
> 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/44ua31425578083.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/5dqgl1425578083.tab") 
> 
> try(system("convert tmp/1b6n61425578083.ps tmp/1b6n61425578083.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gh1n1425578083.ps tmp/2gh1n1425578083.png",intern=TRUE))
character(0)
> try(system("convert tmp/30wj31425578083.ps tmp/30wj31425578083.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.139   0.259   1.406