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Type 'q()' to quit R. > x <- c(112.6,113.8,107.8,103.2,103.3,101.2,107.7,110.4,101.9,115.9,89.9,88.6,117.2,123.9,100,103.6,94.1,98.7,119.5,112.7,104.4,124.7,89.1,97,121.6,118.8,114,111.5,97.2,102.5,113.4,109.8,104.9,126.1,80,96.8,117.2,112.3,117.3,111.1,102.2,104.3,122.9,107.6,121.3,131.5,89,104.4,128.9,135.9,133.3,121.3,120.5,120.4,137.9,126.1,133.2,146.6,103.4,117.2) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > if (par1 == 'Default') { + par1 = 10*log10(length(x)) + } else { + par1 <- as.numeric(par1) + } > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/www/html/rcomp/tmp/17ceu1196512220.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2j6ed1196512220.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF') > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.000000000 -0.570817329 0.074490575 0.160236455 -0.279487524 [6] 0.161244662 0.145351565 -0.276490546 0.110568651 0.152544574 [11] -0.262613763 0.216796991 -0.165776364 -0.005198082 0.079283369 [16] -0.015073804 -0.044008522 0.024928756 0.078889127 -0.208640985 [21] 0.161252170 -0.029305903 -0.064863807 0.179931537 -0.148681038 [26] -0.057358325 0.149245721 -0.036189182 -0.114751380 0.218210038 [31] -0.284132124 0.251954358 -0.040111711 -0.123145154 0.102137663 [36] -0.075000117 0.007236616 > (mypacf <- c(rpacf$acf)) [1] -0.5708173286 -0.3728180586 0.0099892223 -0.2095573225 -0.1686592236 [6] 0.2067679758 0.0141197262 -0.1853352805 0.1704515574 0.0648839280 [11] -0.0315034592 -0.2065065250 -0.0494101137 -0.1294882231 -0.1092648029 [16] -0.0164707906 -0.0477084906 0.1457661898 -0.1325144086 -0.1522094176 [21] 0.0600869683 0.0043117137 0.0692781078 -0.0209631402 -0.0824444264 [26] -0.1002953221 0.0700361199 -0.0573413433 -0.0033081434 -0.1144856792 [31] 0.0975374871 0.0008835374 -0.0097259406 0.0265025001 -0.0430281852 [36] -0.1172712001 > 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/3efjn1196512220.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/48tmf1196512220.tab") > > system("convert tmp/17ceu1196512220.ps tmp/17ceu1196512220.png") > system("convert tmp/2j6ed1196512220.ps tmp/2j6ed1196512220.png") > > > proc.time() user system elapsed 0.815 0.320 0.946