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Type 'q()' to quit R. > x <- c(102.86,102.55,102.28,102.26,102.57,103.08,102.76,102.51,102.87,103.14,103.12,103.16,102.48,102.57,102.88,102.63,102.38,101.69,101.96,102.19,101.87,101.6,101.63,101.22,101.21,101.49,101.64,101.66,101.77,101.82,101.78,101.28,101.29,101.37,101.12,101.51,102.24,102.94,103.09,103.46,103.64,104.39,104.15,105.21,105.8,105.91,105.39,105.46,104.72,103.14,102.63,102.32,101.93,100.62,100.6,99.63,98.9,98.32,99.22,98.81) > par7 = '0.95' > par6 = 'MA' > par5 = '12' > par4 = '0' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: > if (par1 == 'Default') { + par1 = 10*log10(length(x)) + } else { + par1 <- as.numeric(par1) + } > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma' > par7 <- as.numeric(par7) > if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/www/html/rcomp/tmp/1unpj1260465451.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/21ixd1260465451.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.000000000 0.287026505 0.211807739 0.207128336 0.350045974 [6] -0.017537513 0.074285438 0.112567066 -0.016402804 -0.190501098 [11] -0.145085959 0.002970277 -0.415377439 -0.251563142 -0.108018731 [16] 0.007155931 -0.209743778 -0.023135667 -0.061320610 -0.024215700 [21] -0.184304230 -0.031996466 0.044890126 -0.064545847 -0.116016141 [26] 0.041533123 -0.019017301 -0.084571613 0.002575336 0.024733948 [31] 0.020420552 -0.029875947 0.138695038 0.117840466 0.037006475 [36] -0.029143037 0.113108539 > (mypacf <- c(rpacf$acf)) [1] 0.287026505 0.141043263 0.127229591 0.274578961 -0.237470021 [6] 0.037065604 0.054563553 -0.169298931 -0.118631806 -0.136567936 [11] 0.107397025 -0.419203275 0.055385263 0.105144435 0.073083184 [16] 0.123710840 -0.054473800 -0.066943301 0.017450765 -0.206837785 [21] -0.107061215 0.014036065 -0.020764656 -0.195774186 0.080583938 [26] -0.041602587 0.112011684 0.106016919 -0.050891436 0.009555646 [31] -0.007907172 0.040752525 -0.091274845 -0.028292409 -0.058403159 [36] -0.158515332 > 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/3448t1260465452.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/4p7zz1260465452.tab") > system("convert tmp/1unpj1260465451.ps tmp/1unpj1260465451.png") > system("convert tmp/21ixd1260465451.ps tmp/21ixd1260465451.png") > > > proc.time() user system elapsed 0.552 0.313 0.655