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Type 'q()' to quit R. > x <- c(588264,577918,567562,546859,756344,745987,588264,483527,493873,493873,504229,526055,462824,399492,347630,347630,546859,567562,409838,231412,325803,325803,399492,442021,431664,325803,378790,357986,536412,493873,325803,200263,315447,347630,378790,420195,336150,263595,294755,305101,577918,577918,420195,399492,462824,431664,515709,620447,641250,493873,452367,409838,694135,714939,661953,714939,704481,620447,714939,819676,862205,735641,651596,714939,987746,1071790,1051088,1092483,1082137,977399,1155825,1198354,1260562,1071790,998102,1082137,1282389,1460814,1418286,1418286,1439089,1366423,1555307,1555307,1523124,1344597,1376780,1397583,1534503,1712929,1586355,1649698,1596712,1565653,1807421,1754435,1680746,1576009,1680746,1733732,1796963,1880998,1796963,1848826,1785585,1775239,2037699,2059525,1975491,1828123,1953664,2006549,2069882,2164273,2069882,2143570,2111388,1996193,2237951,2237951) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '0' > par3 = '1' > par2 = '0.0' > par1 = '48' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, 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: > #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 (par8 != '') par8 <- as.numeric(par8) > ox <- x > if (par8 == '') { + if (par2 == 0) { + x <- log(x) + } else { + x <- (x ^ par2 - 1) / par2 + } + } else { + x <- log(x,base=par8) + } > if (par3 > 0) x <- diff(x,lag=1,difference=par3) > if (par4 > 0) x <- diff(x,lag=par5,difference=par4) > postscript(file="/var/wessaorg/rcomp/tmp/1a3lz1313157585.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value') > if (par8=='') { + mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='') + mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='') + } else { + mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='') + mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='') + } > plot(x,type='l', main=mytitle,xlab='time',ylab='value') > par(op) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/28jx61313157585.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=mysub) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3v2n61313157585.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',sub=mysub) > dev.off() null device 1 > (myacf <- c(racf$acf)) [1] 1.0000000000 0.0376591576 -0.3159063081 -0.3964020198 -0.0626702803 [6] 0.0767706098 0.4444420217 0.0972340015 0.0157286899 -0.4090588955 [11] -0.3374671164 0.0894483304 0.7655079395 -0.0002656245 -0.2357542528 [16] -0.2798418207 -0.0708693102 0.0351908417 0.3134340284 0.1071758725 [21] 0.0857226601 -0.3787811629 -0.2530847052 0.0946797002 0.4960793518 [26] -0.0021496625 -0.1142938940 -0.1814678888 -0.0974307267 -0.0613120750 [31] 0.2271287548 0.1516909287 0.0971294810 -0.3185784988 -0.2334578561 [36] 0.0377475573 0.3039267479 0.0312730837 -0.0286265969 -0.0814988438 [41] -0.1322219318 -0.1006866136 0.1818178599 0.1573640089 0.0653805720 [46] -0.2311575481 -0.1754581217 0.0102621599 0.2036342500 > (mypacf <- c(rpacf$acf)) [1] 0.0376591576 -0.3177751929 -0.4107603517 -0.2321123377 -0.2924324522 [6] 0.2183837806 0.0495496756 0.3677778343 -0.0595193098 -0.2887146598 [11] -0.1246714795 0.5453814421 -0.1157784438 -0.0344609817 0.1954429077 [16] 0.1062193662 0.0096123155 -0.1504504955 0.0037186865 0.0643268530 [21] -0.0657762546 0.1402130625 -0.0332114330 -0.1456796565 0.0995585321 [26] 0.0944938300 -0.0204648147 -0.1781337299 -0.0946726909 0.0952471516 [31] -0.0143335631 -0.1263899704 0.0071511477 -0.1386520805 -0.1046130918 [36] -0.0359939506 -0.0797944292 -0.2001634595 0.0056209834 0.1036450945 [41] 0.1466414400 -0.0338535537 -0.0325653449 0.0300521969 -0.0030736016 [46] 0.0644373492 -0.0660783061 -0.0006874968 > lengthx <- length(x) > sqrtn <- sqrt(lengthx) > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/4saah1313157585.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/wessaorg/rcomp/tmp/5fw7m1313157585.tab") > > try(system("convert tmp/1a3lz1313157585.ps tmp/1a3lz1313157585.png",intern=TRUE)) character(0) > try(system("convert tmp/28jx61313157585.ps tmp/28jx61313157585.png",intern=TRUE)) character(0) > try(system("convert tmp/3v2n61313157585.ps tmp/3v2n61313157585.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.949 0.176 1.125