R version 2.10.1 (2009-12-14) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(7.24,7.52,7.57,7.59,7.58,7.55,7.52,7.55,7.62,7.64,7.68,7.69,7.7,7.6,7.51,7.66,7.69,7.66,7.7,7.72,7.74,7.76,7.72,7.73,7.75,8.1,8.22,8.32,8.07,8.18,8.33,8.34,8.25,8.36,8.36,8.34,8.41,8.39,8.43,8.44,8.49,8.47,8.53,8.52,8.51,8.53,8.54,8.53,8.47,8.63,8.67,8.73,8.57,8.55,8.63,8.65,8.44,8.62,8.37,8.59,8.84,8.72,8.8,8.69,8.68,8.57,8.85,8.85,8.85,8.93,8.75,8.78,8.77,9.03,9.01,9.07,8.99,9.02,8.99,8.98,8.94,8.94,8.75,8.86) > 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. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > 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/yougetitorg/rcomp/tmp/10rxs1305850108.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/yougetitorg/rcomp/tmp/2e3ey1305850108.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/yougetitorg/rcomp/tmp/3nazh1305850108.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 0.941112381 0.908861394 0.873467019 0.846040970 [6] 0.817024109 0.785623935 0.745820189 0.703141038 0.666534310 [11] 0.626113108 0.589289039 0.557166574 0.526930029 0.493350180 [16] 0.447669640 0.407301336 0.371732535 0.331492132 0.296915241 [21] 0.260783518 0.224567374 0.189226517 0.155658680 0.121573430 [26] 0.074724750 0.056695366 0.033001400 0.026202326 -0.001043095 [31] -0.023288362 -0.043404709 -0.056656188 -0.077717130 -0.092751102 [36] -0.110206848 -0.130623605 -0.148118657 -0.168224120 -0.180678360 [41] -0.196723585 -0.208465854 -0.224533354 -0.240439794 -0.256317530 [46] -0.274627078 -0.287540814 -0.297073124 -0.308054697 > (mypacf <- c(rpacf$acf)) [1] 0.9411123805 0.2026890950 0.0067632282 0.0534225123 0.0019158039 [6] -0.0361266192 -0.0997043621 -0.0857099478 0.0050205237 -0.0494684028 [11] -0.0091211236 0.0415628045 0.0284972147 -0.0268165886 -0.1407187195 [16] -0.0334796514 0.0166321230 -0.0798447413 0.0009211774 -0.0020071340 [21] -0.0096605188 -0.0116540548 -0.0182501053 -0.0158956931 -0.1623103955 [26] 0.1572594155 0.0335654587 0.1404929386 -0.1076090594 -0.0365804417 [31] 0.0184033852 0.0132478552 -0.1265466531 0.0099333707 -0.0167845494 [36] -0.0460065957 -0.0181488113 -0.0051834154 0.0719705240 -0.1026760551 [41] -0.0228922511 -0.0256413237 -0.0246812102 -0.0334126348 -0.0923909030 [46] 0.0392833910 0.0408640145 -0.0400735925 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/yougetitorg/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/yougetitorg/rcomp/tmp/4e2bm1305850108.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/yougetitorg/rcomp/tmp/5uztb1305850108.tab") > > try(system("convert tmp/10rxs1305850108.ps tmp/10rxs1305850108.png",intern=TRUE)) character(0) > try(system("convert tmp/2e3ey1305850108.ps tmp/2e3ey1305850108.png",intern=TRUE)) character(0) > try(system("convert tmp/3nazh1305850108.ps tmp/3nazh1305850108.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.950 0.580 1.214