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Type 'q()' to quit R. > x <- c(1.65,1.66,1.66,1.67,1.68,1.68,1.68,1.68,1.69,1.7,1.7,1.71,1.72,1.73,1.74,1.74,1.75,1.75,1.75,1.76,1.79,1.83,1.84,1.85,1.87,1.87,1.87,1.88,1.88,1.88,1.88,1.89,1.89,1.89,1.9,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.89,1.9,1.9,1.92,1.93,1.92,1.95,1.96,1.96,1.96,1.96,1.96,1.97,1.97,1.97,1.97,1.97,1.97,1.98,1.98,1.98,1.98,1.98,1.98,1.97,1.98,1.98,1.99,2,2) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '1' > par1 = '60' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '0' > par3 <- '1' > par2 <- '1' > par1 <- '60' > #'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/fisher/rcomp/tmp/1h5fo1384808450.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/fisher/rcomp/tmp/2yhxq1384808450.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/fisher/rcomp/tmp/30c041384808450.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 0.230173470 0.124051961 0.283812282 0.030200768 [6] 0.071569262 0.023644110 0.075674533 0.061734276 0.029357769 [11] 0.099824442 0.030575434 0.042845750 0.010469243 -0.169397269 [16] -0.080494345 -0.094434602 -0.079276680 -0.093216937 -0.033412192 [21] -0.068676305 -0.040857343 -0.091670101 -0.079399785 0.011502251 [26] -0.147040405 -0.013490657 -0.048754770 -0.088905600 -0.047537105 [31] -0.013942933 -0.064755691 -0.104906521 0.057741405 0.043801149 [36] -0.022560254 0.158523922 0.118373093 -0.013958990 0.111816435 [41] 0.090101856 0.049951026 -0.045508556 -0.067223135 -0.033628963 [46] 0.018401460 -0.003313119 -0.061900200 0.008566474 -0.020922428 [51] -0.090171437 -0.038141014 0.013889409 -0.073795850 -0.095510429 [56] -0.109450686 -0.075856514 -0.055811875 -0.032879630 -0.007059781 [61] 0.028533503 > (mypacf <- c(rpacf$acf)) [1] 0.2301734704 0.0750481736 0.2549974321 -0.0977452452 0.0539114291 [6] -0.0791774409 0.1176787012 -0.0093417289 0.0394604169 0.0358948987 [11] -0.0056690431 0.0168385619 -0.0442735938 -0.1921506417 -0.0333231452 [16] -0.0567415759 0.0522712775 -0.0873623930 0.0623927258 -0.1073136460 [21] 0.0822786631 -0.1408095464 0.0532957773 0.0226964044 -0.0720089428 [26] 0.0754994596 -0.0714712908 -0.0102387502 -0.0892221733 0.0775243978 [31] -0.1080754739 -0.0439048323 0.1163583246 0.0186154259 0.0437596309 [36] 0.0805239043 0.0791734447 -0.0847114805 0.0744862255 0.0332083952 [41] 0.0124042282 -0.1284705816 -0.1543692632 0.0036273559 0.0008658703 [46] -0.0111482536 -0.1221962315 0.0376200071 -0.0340549446 -0.0301596699 [51] 0.0631319638 0.0245561564 0.0114555993 -0.0836193644 -0.0111431083 [56] -0.0666853321 -0.0246610169 0.0351183684 0.0256692435 0.0328528944 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/4ho3x1384808450.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/fisher/rcomp/tmp/5yru91384808450.tab") > > try(system("convert tmp/1h5fo1384808450.ps tmp/1h5fo1384808450.png",intern=TRUE)) character(0) > try(system("convert tmp/2yhxq1384808450.ps tmp/2yhxq1384808450.png",intern=TRUE)) character(0) > try(system("convert tmp/30c041384808450.ps tmp/30c041384808450.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.072 0.474 2.528