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(790,766,1040,949,758,1023,921,775,907,835,871,836,789,811,996,778,603,990,735,800,706,766,870,647,726,784,884,696,893,674,703,799,793,799,1022,758,1021,944,915,864,1022,891,1087,822,890,1092,967,833,1104,1063,1103,1039,1185,1047,1155,878,879,1133,920,943,938,900,781,1040,792,653,866,679,799,760,697,750)
> 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/1cclu1425547027.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/25u7t1425547027.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/31oya1425547027.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 -0.565818537 -0.041152428  0.222417262 -0.057944728
 [6] -0.097648730  0.196145514 -0.238891388  0.082073420  0.224492410
[11] -0.305352945  0.018174519  0.349917140 -0.430179355  0.226013281
[16] -0.007231838 -0.094162181  0.092626168 -0.028051032 -0.093055989
[21]  0.137896463 -0.035032968 -0.185074999  0.238156234 -0.056515899
[26] -0.143908272  0.183952715 -0.129780820  0.047247808  0.046711941
[31] -0.166200373  0.099507793  0.110521290 -0.152658459 -0.040702791
[36]  0.194949779 -0.167238990  0.086117410 -0.010860458 -0.111132345
[41]  0.226721220 -0.179146267  0.002689652  0.079646832  0.012441366
[46] -0.134844420  0.147338566 -0.015159285 -0.127477518
> (mypacf <- c(rpacf$acf))
 [1] -5.658185e-01 -5.314457e-01 -2.335701e-01  7.683336e-05 -3.057323e-03
 [6]  2.329311e-01 -5.292575e-02 -1.885569e-01  1.647742e-01  7.899704e-02
[11] -1.456952e-01  2.213851e-01 -8.632280e-02  2.406862e-02 -6.148611e-02
[16] -3.119042e-02  5.559286e-02 -1.253900e-01  1.246707e-03 -1.803843e-02
[21] -8.800289e-02 -1.562594e-01 -8.199935e-02 -1.894650e-03  2.525346e-02
[26]  1.846837e-02 -2.893870e-02 -3.999336e-02 -2.024963e-02 -1.553868e-01
[31] -1.401874e-01  2.253862e-02  1.135872e-01  1.558490e-04 -3.281670e-02
[36] -7.984485e-02  2.161035e-02  3.450870e-02 -4.099756e-02  1.368042e-01
[41] -9.989188e-02 -5.559509e-03 -8.085504e-02 -4.105072e-02 -4.928253e-02
[46]  2.258153e-02  1.647112e-01 -4.860171e-02
> 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/48sk31425547027.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/5scxj1425547027.tab") 
> 
> try(system("convert tmp/1cclu1425547027.ps tmp/1cclu1425547027.png",intern=TRUE))
character(0)
> try(system("convert tmp/25u7t1425547027.ps tmp/25u7t1425547027.png",intern=TRUE))
character(0)
> try(system("convert tmp/31oya1425547027.ps tmp/31oya1425547027.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.172   0.232   1.411