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Type 'q()' to quit R. > x <- c(627,696,825,677,656,785,412,352,839,729,696,641,695,638,762,635,721,854,418,367,824,687,601,676,740,691,683,594,729,731,386,331,707,715,657,653,642,643,718,654,632,731,392,344,792,852,649,629,685,617,715,715,629,916,531,357,917,828,708,858,775,785,1006,789,734,906,532,387,991,841) > par7 = '' > par6 = 'White Noise' > par5 = '12' > par4 = '1' > par3 = '0' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > if (par1 == 'Default') { + par1 = 10*log10(length(x)) + } else { + par1 <- as.numeric(par1) + } > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/www/html/rcomp/tmp/1e2tn1260532272.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/23f1f1260532272.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.00000000 0.38710710 0.21887458 0.32087156 0.07644618 0.21412905 [7] 0.29861608 0.14595199 0.33395112 0.24959331 0.10251973 0.16031082 [13] -0.07261909 -0.10665524 0.13982262 0.07174923 -0.01907111 0.09092928 [19] 0.02919674 -0.07013365 0.01143377 -0.08227136 -0.14142589 -0.08943930 [25] -0.23191101 -0.12155332 -0.12029127 -0.17893825 -0.04727354 -0.08077697 [31] -0.24025726 -0.19356267 -0.26188197 -0.19810366 -0.08078832 -0.09901667 [37] -0.05593430 > (mypacf <- c(rpacf$acf)) [1] 0.387107097 0.081188997 0.250542003 -0.159698463 0.238084754 [6] 0.110511765 0.018438577 0.226295274 -0.021545933 -0.002356247 [11] -0.056376757 -0.232899288 -0.106979144 0.111317814 0.044138354 [16] -0.160923319 0.063735435 0.094073486 -0.108358644 0.081834762 [21] -0.023417137 -0.118905239 -0.109378917 -0.220732033 0.010819113 [26] -0.126787855 0.137858245 0.015358419 0.031936196 -0.016321648 [31] -0.090841628 -0.073099336 0.092405795 0.027301047 -0.018695745 [36] -0.041247980 > 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/393fj1260532272.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/4cgdt1260532273.tab") > > system("convert tmp/1e2tn1260532272.ps tmp/1e2tn1260532272.png") > system("convert tmp/23f1f1260532272.ps tmp/23f1f1260532272.png") > > > proc.time() user system elapsed 0.537 0.313 0.708