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Type 'q()' to quit R. > x <- c(155.28,173.24,180.16,181.52,182.25,182.19,182,181.65,180.07,182.62,180.38,181.15,180.5,181.14,180.93,211.91,223.81,226.88,226.8,231.81,232.06,232.32,228.37,226.31,225.72,219.98,219.31,215.19,213.81,213.7,213.6,213.52,218.39,219.97,221.09,219.17,219.17,218.45,216.88,216.19,214.59,269.87,272.71,280.35,274.5,268.86,261.7,263.98,263.01,262.79,263.59,267,267.89,267.86,266.84,268.24,267.67,269.07,270.87,271.68,271.63,275.21,276.66,276.08,278.3,279.06,279.28,279.12,262.72,262.55,260.7,259.14,260.61,260.53,259.07,257.01,257.08,256.83,256.75,257.61,258.58,259.57,259.29,258.51) > 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/wessaorg/rcomp/tmp/18aeo1384768820.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/2t9a41384768820.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/36jpu1384768820.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] 1.000000e+00 1.122954e-01 9.629881e-02 -1.016654e-01 -6.334758e-02 [6] -1.173553e-01 -2.747640e-02 -6.989893e-02 -1.923770e-02 1.042905e-02 [11] -2.197544e-02 -3.193090e-02 -5.291870e-02 -2.630987e-02 7.062028e-02 [16] 2.464629e-02 -5.922119e-02 2.748509e-02 -5.977426e-03 -4.406672e-02 [21] 6.203067e-03 -1.927077e-02 3.885445e-02 1.167429e-02 1.751559e-02 [26] 6.722116e-02 2.920326e-01 -1.853670e-01 1.591172e-02 -9.217100e-02 [31] -6.352622e-02 -4.883494e-02 2.410355e-02 -5.904186e-02 -5.519001e-02 [36] -2.728450e-02 -2.607834e-02 -2.315007e-02 9.521776e-05 4.854505e-02 [41] 1.951663e-01 1.238928e-02 1.268745e-02 3.925297e-03 -1.865453e-02 [46] -5.829209e-03 4.549981e-02 3.165449e-03 4.462178e-03 5.241012e-03 [51] 1.454380e-02 -1.294667e-02 -4.261081e-02 -1.039684e-01 -8.200322e-03 [56] -2.044946e-02 -3.909094e-03 7.178006e-03 6.612804e-05 -2.400686e-02 [61] 2.003407e-03 > (mypacf <- c(rpacf$acf)) [1] 0.1122953649 0.0847573686 -0.1235143016 -0.0490487240 -0.0865034218 [6] -0.0074433894 -0.0608610828 -0.0283746422 0.0140224589 -0.0471615218 [11] -0.0437990016 -0.0550241138 -0.0226367813 0.0748571926 -0.0109433159 [16] -0.0980158442 0.0406900883 -0.0013396099 -0.0641232999 0.0133100995 [21] -0.0178402085 0.0376417292 -0.0145616045 -0.0057801742 0.0860664924 [26] 0.2975703096 -0.2907314807 0.0219855020 0.0383660622 -0.0627456992 [31] -0.0041128594 0.0007391028 -0.0284134043 -0.0822562506 -0.0476693540 [36] -0.0043919349 -0.0077812829 0.0073627054 -0.0033605260 0.1428166116 [41] -0.0236985645 0.0089826333 -0.0194724973 0.0386615715 0.0474081474 [46] -0.0049242142 0.0215085012 -0.0065366469 0.0235504390 0.0309540379 [51] -0.0585024661 -0.0854615391 0.0807517216 -0.1037503772 0.0238396101 [56] 0.0615777494 -0.0614672315 -0.0282747038 0.0280786700 0.0092752132 > 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/4hkal1384768820.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/5vs0k1384768820.tab") > > try(system("convert tmp/18aeo1384768820.ps tmp/18aeo1384768820.png",intern=TRUE)) character(0) > try(system("convert tmp/2t9a41384768820.ps tmp/2t9a41384768820.png",intern=TRUE)) character(0) > try(system("convert tmp/36jpu1384768820.ps tmp/36jpu1384768820.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.717 0.572 3.291