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(950,775,805,680,705,755,715,860,900,1010,925,650,1060,1050,1025,1085,1160,1310,1445,1445,1615,1650,1255,1175,1300,1280,1390,1340,1110,1325,1265,1150,1430,1655,1570,1345,1430,1260,1495,1125,895,1085,870,1185,1455,1540,1615,1200,1260,1095,1160,1095,1300,1215,1245,1350,1300,1280,1270,1065,1340,1265,1155,930,880,925,980,1015,1040,1365,1160,1115,1630,1225,1200,1265,1140,1270,1445,1305,1665,1830,1690,1520)
> 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/13z9j1425566797.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/25po61425566797.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/3xtxh1425566797.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  0.732356224  0.560779302  0.439695712  0.247858241
 [6]  0.205354850  0.145075116  0.098376124  0.139001301  0.118567700
[11]  0.057987982  0.085281225  0.075477444 -0.056748707 -0.093977262
[16] -0.191211752 -0.213906181 -0.189753442 -0.247262502 -0.216123534
[21] -0.159136642 -0.166428857 -0.130366214 -0.074220373 -0.013091634
[26]  0.009254760  0.023701451 -0.042296014 -0.055630731 -0.143956450
[31] -0.233815568 -0.180624512 -0.203783402 -0.143653109 -0.014490305
[36]  0.030859630  0.114469190  0.081066405 -0.008657205 -0.019139814
[41] -0.070987147 -0.146633689 -0.109450932 -0.094718096 -0.084413252
[46] -0.025430432  0.003074658  0.041282256  0.105362239
> (mypacf <- c(rpacf$acf))
 [1]  0.732356224  0.052698012  0.026070952 -0.205787013  0.158757284
 [6] -0.043072673  0.030332059  0.094774446 -0.021094385 -0.121224866
[11]  0.114442537  0.021482000 -0.293250511  0.010408607 -0.118792188
[16]  0.090338218 -0.076738035 -0.064730590 -0.009670962  0.050772064
[21] -0.022874771  0.021255258  0.067272323  0.116271644 -0.056570929
[26]  0.029392665 -0.136276612 -0.036552593 -0.228149812 -0.024275425
[31]  0.079139376 -0.148313488  0.111525802  0.163249242  0.045386367
[36] -0.030457047 -0.118288914 -0.060248005  0.106484079 -0.109254630
[41] -0.031275227  0.051336829 -0.049897600 -0.038795660 -0.058034230
[46]  0.102468806 -0.050507670  0.025437972
> 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/412i51425566797.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/5oydk1425566797.tab") 
> 
> try(system("convert tmp/13z9j1425566797.ps tmp/13z9j1425566797.png",intern=TRUE))
character(0)
> try(system("convert tmp/25po61425566797.ps tmp/25po61425566797.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xtxh1425566797.ps tmp/3xtxh1425566797.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.172   0.212   1.385