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Type 'q()' to quit R. > x <- c(93.5,94.7,112.9,99.2,105.6,113,83.1,81.1,96.9,104.3,97.7,102.6,89.9,96,112.7,107.1,106.2,121,101.2,83.2,105.1,113.3,99.1,100.3,93.5,98.8,106.2,98.3,102.1,117.1,101.5,80.5,105.9,109.5,97.2,114.5,93.5,100.9,121.1,116.5,109.3,118.1,108.3,105.4,116.2,111.2,105.8,122.7,99.5,107.9,124.6,115,110.3,132.7,99.7,96.5,118.7,112.9,130.5,137.9,115,116.8,140.9,120.7,134.2,147.3,112.4,107.1,128.4,137.7,135,151,137.4,132.4,161.3,139.8,146,154.6,142.1,120.5) > par5 = '12' > par4 = '1' > par3 = '1' > par2 = '1' > par1 = '36' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > if (par1 == 'Default') { + par1 = 10*log10(length(x)) + } else { + par1 <- as.numeric(par1) + } > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/www/html/rcomp/tmp/1qhb41196278456.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2dp171196278456.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.00000000 -0.40772118 -0.17089548 0.10073107 0.02027898 0.03147298 [7] -0.01608500 0.03505840 -0.14439195 0.08691983 -0.03166986 0.09877549 [13] -0.18839548 -0.04157208 0.17585129 -0.03352795 0.01003765 -0.12774055 [19] 0.09363634 -0.04225632 0.01651210 0.02834106 0.03935731 0.04298132 [25] -0.23774153 0.20042284 0.08691021 -0.17921287 0.02387556 0.11630667 [31] -0.05007380 -0.02981509 0.04578165 -0.10301620 0.02632870 0.08947780 [37] -0.05278064 > (mypacf <- c(rpacf$acf)) [1] -0.407721182 -0.404349757 -0.232251944 -0.150201138 -0.015640020 [6] 0.029831328 0.120115557 -0.089926786 -0.043841945 -0.148417992 [11] 0.043224072 -0.188510161 -0.267790931 -0.147006406 -0.069421674 [16] 0.052757230 -0.073390241 -0.022819690 -0.122509814 -0.194019948 [21] -0.208048195 -0.058285460 0.168446199 -0.153034983 -0.133981707 [26] 0.066536783 -0.057466873 -0.086541790 -0.029726703 0.009812647 [31] 0.032844391 -0.021250310 -0.071117580 -0.057882586 0.106647776 [36] -0.082300064 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > load(file='/var/www/html/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 1:par1) { + 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(mytstat,lengthx),6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/3gvgu1196278456.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-1,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(mytstat,lengthx),6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4xmtc1196278456.tab") > > system("convert tmp/1qhb41196278456.ps tmp/1qhb41196278456.png") > system("convert tmp/2dp171196278456.ps tmp/2dp171196278456.png") > > > proc.time() user system elapsed 0.842 0.328 0.945