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Type 'q()' to quit R. > x <- c(562.325,560.854,555.332,543.599,536.662,542.722,593.530,610.763,612.613,611.324,594.167,595.454,590.865,589.379,584.428,573.100,567.456,569.028,620.735,628.884,628.232,612.117,595.404,597.141,593.408,590.072,579.799,574.205,572.775,572.942,619.567,625.809,619.916,587.625,565.742,557.274,560.576,548.854,531.673,525.919,511.038,498.662,555.362,564.591,541.657,527.070,509.846,514.258,516.922,507.561,492.622,490.243,469.357,477.580,528.379,533.590,517.945,506.174,501.866,516.141,528.222,532.638,536.322,536.535,523.597,536.214,586.570,596.594,580.523,564.478,557.560,575.093) > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '0' > par2 = '1' > par1 = 'Default' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: > if (par1 == 'Default') { + par1 = 10*log10(length(x)) + } else { + par1 <- as.numeric(par1) + } > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma' > par7 <- as.numeric(par7) > if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/www/html/rcomp/tmp/1vlcf1291711622.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2vlcf1291711622.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.00000000 0.89021679 0.72575125 0.61169479 0.56416637 0.56159861 [7] 0.53800328 0.47865048 0.40709419 0.37757856 0.40476640 0.47634001 [13] 0.49216309 0.34383784 0.16618614 0.04032720 -0.01773884 -0.03287308 [19] -0.06490751 > (mypacf <- c(rpacf$acf)) [1] 0.89021679 -0.32159112 0.23720349 0.12878501 0.13002797 -0.11846109 [7] -0.01821537 -0.02077591 0.17308537 0.11778164 0.22939694 -0.26144306 [13] -0.65679651 0.12762850 -0.10539472 -0.06041560 -0.02651782 0.05251798 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > 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 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/html/rcomp/tmp/39va61291711622.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/html/rcomp/tmp/4uw9c1291711622.tab") > > try(system("convert tmp/1vlcf1291711622.ps tmp/1vlcf1291711622.png",intern=TRUE)) character(0) > try(system("convert tmp/2vlcf1291711622.ps tmp/2vlcf1291711622.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.524 0.328 1.484