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Type 'q()' to quit R. > x <- c(336.02,333.15,314.95,302.48,307.31,305.50,308.57,322.58,337.09,323.81,333.06,331.90,327.90,319.93,331.51,336.42,319.77,323.20,324.51,328.34,331.88,336.45,337.95,330.75,323.87,325.26,328.73,331.72,332.54,354.25,352.69,356.15,372.50,390.90,404.65,430.04,453.54,464.98,463.31,497.20,528.62,470.91,499.53,493.51,469.97,464.41,487.15,476.45,484.91,509.61,495.19,504.75,493.43,488.58,484.82,488.46,512.32,530.29,549.38,551.45,604.41,625.29,623.56,577.42,572.28,571.69,596.28,560.00,577.93,606.51,597.31,607.58,648.14,737.48,708.73,674.01,679.90,674.93,663.38,665.69,684.21,703.71,755.42,772.43) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '1' > par1 = 'Default' > #'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/www/rcomp/tmp/1qkd21293209707.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/www/rcomp/tmp/2bmf01293209708.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/www/rcomp/tmp/3bmf01293209708.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] 1.00000000 0.05553775 -0.13974662 0.05607343 0.09879080 -0.22700187 [7] -0.20914899 0.01168560 -0.07780564 0.05734305 -0.04680628 0.15016984 [13] 0.10092525 0.12913188 -0.02628405 -0.06657019 -0.03842871 -0.05779929 [19] -0.07546291 -0.17809546 > (mypacf <- c(rpacf$acf)) [1] 0.055537748 -0.143272981 0.074661834 0.071883658 -0.228161427 [6] -0.169282199 -0.035310751 -0.121129472 0.133728065 -0.110569794 [11] 0.126557891 0.042035105 0.115750956 -0.017670334 -0.067747739 [16] -0.051399989 0.009011766 -0.032327826 -0.108128673 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/www/rcomp/tmp/4f4d61293209708.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/www/rcomp/tmp/5imct1293209708.tab") > > try(system("convert tmp/1qkd21293209707.ps tmp/1qkd21293209707.png",intern=TRUE)) character(0) > try(system("convert tmp/2bmf01293209708.ps tmp/2bmf01293209708.png",intern=TRUE)) character(0) > try(system("convert tmp/3bmf01293209708.ps tmp/3bmf01293209708.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.820 0.240 1.031