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(1143,1162,1169,1184,1169,1189,1192,1198,1168,1179,1173,1172,1125,1127,1123,1132,1114,1127,1129,1139,1117,1131,1132,1140,1105,1126,1129,1139,1123,1101,1110,1128,1101,1134,1139,1137,1141,1165,1146,1134,1141,1159,1166,1192,1171,1179,1181,1195,1167,1176,1181,1197,1194,1173,1179,1184,1193,1193,1193,1191,1222,1198,1218,1219,1260,1235,1256,1258,1295,1294,1318,1262)
> 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/1m25b1413637738.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/2o4h81413637738.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/3qej41413637738.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  0.892719485  0.812081615  0.716462329  0.675249108
 [6]  0.578858722  0.532721469  0.458937470  0.429429710  0.370991779
[11]  0.341747670  0.294020850  0.279522717  0.243216463  0.221210729
[16]  0.191217462  0.178128832  0.147176392  0.123622887  0.097805539
[21]  0.067377962  0.021915334 -0.009326181 -0.026224685 -0.039877534
[26] -0.088060257 -0.117398403 -0.147336641 -0.182769400 -0.225346500
[31] -0.255230754 -0.274717352 -0.273829365 -0.279871523 -0.303138042
[36] -0.327046100 -0.333207719 -0.337350687 -0.353046219 -0.349098561
[41] -0.333988764 -0.320130002 -0.309549981 -0.292052352 -0.291798937
[46] -0.283210053 -0.288027994 -0.271075081 -0.258253158
> (mypacf <- c(rpacf$acf))
 [1]  0.892719485  0.074530374 -0.104008674  0.201804253 -0.256868638
 [6]  0.151958595 -0.086689553  0.065316096 -0.018819928 -0.025021538
[11]  0.029180634  0.014250140 -0.011181014 -0.034489822  0.036792424
[16] -0.022378493 -0.031530664 -0.023826380  0.008651466 -0.096968328
[21] -0.066383335  0.025537628  0.039173915 -0.008512340 -0.197272249
[26]  0.076953573 -0.069773907 -0.126809281  0.030117821 -0.075616417
[31]  0.057957210  0.040582061 -0.037220995 -0.119039820 -0.044481997
[36]  0.020924785  0.002579393 -0.076630346  0.081555681  0.035959946
[41] -0.035704560  0.028722677 -0.036108262 -0.049492897  0.020685127
[46] -0.083024195  0.093701386  0.006894649
> 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/42p0e1413637738.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/5kax91413637738.tab") 
> 
> try(system("convert tmp/1m25b1413637738.ps tmp/1m25b1413637738.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o4h81413637738.ps tmp/2o4h81413637738.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qej41413637738.ps tmp/3qej41413637738.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.165   0.179   1.353