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Type 'q()' to quit R. > x <- c(9676,8642,9402,9610,9294,9448,10319,9548,9801,9596,8923,9746,9829,9125,9782,9441,9162,9915,10444,10209,9985,9842,9429,10132,9849,9172,10313,9819,9955,10048,10082,10541,10208,10233,9439,9963,10158,9225,10474,9757,10490,10281,10444,10640,10695,10786,9832,9747,10411,9511,10402,9701,10540,10112,10915,11183,10384,10834,9886,10216,10943,9867,10203,10837,10573,10647,11502,10656,10866,10835,9945,10331) > par8 = '' > par7 = '0.95' > par6 = 'White Noise' > par5 = '12' > par4 = '1' > par3 = '0' > par2 = '0.0' > par1 = '36' > #'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/1e74r1323794406.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/2qxb21323794406.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/32moq1323794406.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] 1.000000000 -0.142629179 -0.080824369 -0.001132338 -0.072975324 [6] 0.225195110 0.019078341 -0.308783185 -0.093985735 0.166583277 [11] -0.135224680 -0.068886422 -0.149691784 -0.100323353 0.194258069 [16] 0.057009832 -0.146507546 0.120222574 0.081749426 0.103877327 [21] 0.020747203 0.045180236 -0.019125766 0.163185020 -0.131254942 [26] -0.183523722 0.021493465 0.085826323 -0.061087060 -0.129688913 [31] -0.135967031 -0.060522873 0.238905109 -0.049964977 -0.125568683 [36] 0.126467123 -0.047031055 > (mypacf <- c(rpacf$acf)) [1] -0.142629179 -0.103268246 -0.029487725 -0.088896474 0.205003968 [6] 0.074429143 -0.279209392 -0.201578575 0.135987680 -0.176596419 [11] -0.205936131 -0.111154425 -0.078310822 -0.038679158 0.026762853 [16] -0.051479701 0.099820656 0.060661030 0.054609923 -0.078848616 [21] 0.178482689 0.032988389 0.049653623 -0.151360101 -0.114266481 [26] -0.059654663 0.174328739 -0.075412435 -0.092682827 -0.033280924 [31] -0.055473383 0.008472024 0.050814148 -0.039114352 0.103967690 [36] -0.214306156 > 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/4osr71323794406.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/5wueg1323794406.tab") > > try(system("convert tmp/1e74r1323794406.ps tmp/1e74r1323794406.png",intern=TRUE)) character(0) > try(system("convert tmp/2qxb21323794406.ps tmp/2qxb21323794406.png",intern=TRUE)) character(0) > try(system("convert tmp/32moq1323794406.ps tmp/32moq1323794406.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.055 0.230 1.282