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(567,557,547,527,729,719,567,466,476,476,486,507,446,385,335,335,527,547,395,223,314,314,385,426,416,314,365,345,517,476,314,193,304,335,365,405,324,254,284,294,557,557,405,385,446,416,497,598,618,476,436,395,669,689,638,689,679,598,689,790,831,709,628,689,952,1033,1013,1053,1043,942,1114,1155,1215,1033,962,1043,1236,1408,1367,1367,1387,1317,1499,1499,1468,1296,1327,1347,1479,1651,1529,1590,1539,1509,1742,1691,1620,1519,1620,1671,1732,1813,1732,1782,1721,1711,1964,1985,1904,1762,1883,1934,1995,2086,1995,2066,2035,1924,2157,2157)
> 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/1b35f1404765614.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/2ycts1404765614.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/3enpb1404765614.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  0.018824549 -0.301986004 -0.309541444 -0.140978471
 [6]  0.190852603  0.300883386  0.175921974 -0.089054299 -0.332194097
[11] -0.286095534  0.065177671  0.798075195  0.003712058 -0.253146964
[16] -0.244844689 -0.117961955  0.127749920  0.273777856  0.152474509
[21] -0.087003376 -0.325826062 -0.188697704  0.079860088  0.605627502
[26] -0.041276289 -0.189777761 -0.144880920 -0.140591100  0.033656248
[31]  0.280753672  0.155529892 -0.050006238 -0.330126900 -0.180607622
[36]  0.077294228  0.424389395 -0.026066830 -0.115765325 -0.068780263
[41] -0.163475163 -0.056741915  0.274997293  0.183463051 -0.016867859
[46] -0.316541882 -0.159935684  0.038171240  0.317651873
> (mypacf <- c(rpacf$acf))
 [1]  0.018824549 -0.302447544 -0.326406917 -0.304052574 -0.070767219
 [6]  0.095333208  0.211288178  0.185086855 -0.031076584 -0.240320447
[11] -0.235228752  0.676253082 -0.030330976  0.081409580  0.126610917
[16]  0.182792799 -0.102700501  0.015301555 -0.035769911 -0.122721377
[21] -0.096017313  0.175508652 -0.048412824 -0.064577009 -0.054911124
[26]  0.100501038  0.054747124 -0.125445081 -0.166637147  0.074903391
[31]  0.059856766  0.106054768 -0.059086572 -0.134806870 -0.082886455
[36] -0.121528135  0.009806402 -0.133603789 -0.005208128  0.023961038
[41]  0.085699334  0.061353937  0.090621170 -0.034845544 -0.019587857
[46]  0.038986759 -0.023294621 -0.016508772
> 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/47h801404765614.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/5kn2u1404765614.tab") 
> 
> try(system("convert tmp/1b35f1404765614.ps tmp/1b35f1404765614.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ycts1404765614.ps tmp/2ycts1404765614.png",intern=TRUE))
character(0)
> try(system("convert tmp/3enpb1404765614.ps tmp/3enpb1404765614.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.142   0.195   1.342