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Type 'q()' to quit R. > x <- c(100.57,100.27,100.27,100.18,100.16,100.18,100.18,100.59,100.69,101.06,101.15,101.16,101.16,100.81,100.94,101.13,101.29,101.34,101.35,101.7,102.05,102.48,102.66,102.72,102.73,102.18,102.22,102.37,102.53,102.61,102.62,103,103.17,103.52,103.69,103.73,99.57,99.09,99.14,99.36,99.6,99.65,99.8,100.15,100.45,100.89,101.13,101.17,101.21,101.1,101.17,101.11,101.2,101.15,100.92,101.1,101.22,101.25,101.39,101.43,101.95,101.92,102.05,102.07,102.1,102.16,101.63,101.43,101.4,101.6,101.72,101.73) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '1' > par1 = '48' > par8 <- '' > par7 <- '0.95' > par6 <- 'White Noise' > par5 <- '12' > par4 <- '0' > par3 <- '1' > par2 <- '1' > par1 <- '48' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000) > #Author: root > #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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) > x <- na.omit(x) > 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/12z6a1457431369.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/23mr01457431369.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/301ja1457431369.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] 1.0000000000 0.1478976205 -0.0039757127 -0.1101931741 -0.0912607595 [6] -0.0665370577 -0.0730837774 -0.0784991351 -0.1081295555 -0.1181405912 [11] -0.0287473918 0.1328089723 0.0913268193 0.0602053887 -0.0159389601 [16] -0.0591685680 -0.0865181801 -0.0344542158 0.0273674992 -0.0359567186 [21] -0.0637352570 -0.0515335658 -0.0407829088 0.0674400131 -0.0373380398 [26] 0.0370031703 -0.0189176664 -0.0677058439 -0.0230582461 -0.0535671191 [31] 0.1040233932 0.0483656639 0.0030992509 -0.0299540818 -0.0164467114 [36] 0.0516262869 0.0307156005 0.0107820830 0.0114833275 0.0054420869 [41] 0.0028659780 0.0282059087 -0.0031096232 -0.0002733332 -0.0146989989 [46] -0.0184605870 -0.0085985804 -0.0223073294 0.0081778134 > (mypacf <- c(rpacf$acf)) [1] 0.1478976205 -0.0264274859 -0.1081199179 -0.0609686504 -0.0478923694 [6] -0.0721816115 -0.0786718087 -0.1113154872 -0.1237133895 -0.0390589394 [11] 0.0964842663 0.0060122812 0.0042958049 -0.0373721733 -0.0637053596 [16] -0.0865225109 -0.0304108929 0.0188061975 -0.0556635305 -0.0534730129 [21] -0.0443293396 -0.0809272824 0.0194577312 -0.1276669022 -0.0060178690 [26] -0.0544292775 -0.0932784541 -0.0465851197 -0.1220343817 0.0628262375 [31] -0.0290116911 -0.0525256856 -0.0568455571 -0.0619844354 0.0234806705 [36] -0.0559478961 -0.0320779443 -0.0017108347 0.0002873437 0.0026623883 [41] -0.0290732046 -0.0382797928 -0.0395843988 -0.0263426373 -0.0187478087 [46] -0.0400377549 -0.0247046621 -0.0476911121 > 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/4xugj1457431369.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/5ixju1457431369.tab") > > try(system("convert tmp/12z6a1457431369.ps tmp/12z6a1457431369.png",intern=TRUE)) character(0) > try(system("convert tmp/23mr01457431369.ps tmp/23mr01457431369.png",intern=TRUE)) character(0) > try(system("convert tmp/301ja1457431369.ps tmp/301ja1457431369.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.132 0.232 1.373