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Type 'q()' to quit R. > x <- c(77.7,78.89,90.2,77.26,80.76,84.93,66.08,71.56,80.78,83.31,85.3,73.94,78.7,81.32,86.8,80.76,84.46,84.21,73.64,70.85,83.78,89.12,78.93,80.54,81.67,82.53,88.2,89.17,83.7,89.79,77.58,70.11,88.07,92.49,83.33,90.05,82.91,88.52,96.42,90.87,86.4,97.47,85.67,79.91,95.73,94.6,91.92,90.38,82.31,87.82,101.29,89.58,87.83,99.95,82.67,84.65,97.83,97.47,97.66,99.14,90.02,100.97,112.48,91.44,108.46,98.41,89.35,92.8,100.43,104.85,108.36,101.54,105.26,101.8,112.36,99.5,104.65,101.13,89.8,87.84,96.41,103.26,100.31,92.33,96.19,96.37,103.06,101.5,101.88,100.85,95.56,87.6,101.18,110.8,101.1,104.42,103.27,100.87,107.8,104.99,100.76,104.46,100.62,87.84,107.31,115.61,103.43,109.93,104.43,106.69,123.1,109.42,101.46,124.48,101.49,100.46,115.51,113.37,115.4,118.2,106.82,110.17,119.91,112.31,110.62,120.37,97.94,103.02,116.36,108.51,122.54,121.32,112.25,109.89,129.58,107.2,118.68,118.25,102.67,104.19,117.74,123.3,122.2,112.71,118.53,115.32,127.36,110.45,122.22,123.39,116.2,109.22,116.98,132.89,125.24,115.68) > par9 = '1' > par8 = '2' > par7 = '1' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '0' > par2 = '0.3' > par1 = 'FALSE' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > if (par1 == 'TRUE') par1 <- TRUE > if (par1 == 'FALSE') par1 <- FALSE > par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial > par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial > par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial > par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial > armaGR <- function(arima.out, names, n){ + try1 <- arima.out$coef + try2 <- sqrt(diag(arima.out$var.coef)) + try.data.frame <- data.frame(matrix(NA,ncol=4,nrow=length(names))) + dimnames(try.data.frame) <- list(names,c('coef','std','tstat','pv')) + try.data.frame[,1] <- try1 + for(i in 1:length(try2)) try.data.frame[which(rownames(try.data.frame)==names(try2)[i]),2] <- try2[i] + try.data.frame[,3] <- try.data.frame[,1] / try.data.frame[,2] + try.data.frame[,4] <- round((1-pt(abs(try.data.frame[,3]),df=n-(length(try2)+1)))*2,5) + vector <- rep(NA,length(names)) + vector[is.na(try.data.frame[,4])] <- 0 + maxi <- which.max(try.data.frame[,4]) + continue <- max(try.data.frame[,4],na.rm=TRUE) > .05 + vector[maxi] <- 0 + list(summary=try.data.frame,next.vector=vector,continue=continue) + } > arimaSelect <- function(series, order=c(13,0,0), seasonal=list(order=c(2,0,0),period=12), include.mean=F){ + nrc <- order[1]+order[3]+seasonal$order[1]+seasonal$order[3] + coeff <- matrix(NA, nrow=nrc*2, ncol=nrc) + pval <- matrix(NA, nrow=nrc*2, ncol=nrc) + mylist <- rep(list(NULL), nrc) + names <- NULL + if(order[1] > 0) names <- paste('ar',1:order[1],sep='') + if(order[3] > 0) names <- c( names , paste('ma',1:order[3],sep='') ) + if(seasonal$order[1] > 0) names <- c(names, paste('sar',1:seasonal$order[1],sep='')) + if(seasonal$order[3] > 0) names <- c(names, paste('sma',1:seasonal$order[3],sep='')) + arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML') + mylist[[1]] <- arima.out + last.arma <- armaGR(arima.out, names, length(series)) + mystop <- FALSE + i <- 1 + coeff[i,] <- last.arma[[1]][,1] + pval [i,] <- last.arma[[1]][,4] + i <- 2 + aic <- arima.out$aic + while(!mystop){ + mylist[[i]] <- arima.out + arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML', fixed=last.arma$next.vector) + aic <- c(aic, arima.out$aic) + last.arma <- armaGR(arima.out, names, length(series)) + mystop <- !last.arma$continue + coeff[i,] <- last.arma[[1]][,1] + pval [i,] <- last.arma[[1]][,4] + i <- i+1 + } + list(coeff, pval, mylist, aic=aic) + } > arimaSelectplot <- function(arimaSelect.out,noms,choix){ + noms <- names(arimaSelect.out[[3]][[1]]$coef) + coeff <- arimaSelect.out[[1]] + k <- min(which(is.na(coeff[,1])))-1 + coeff <- coeff[1:k,] + pval <- arimaSelect.out[[2]][1:k,] + aic <- arimaSelect.out$aic[1:k] + coeff[coeff==0] <- NA + n <- ncol(coeff) + if(missing(choix)) choix <- k + layout(matrix(c(1,1,1,2, + 3,3,3,2, + 3,3,3,4, + 5,6,7,7),nr=4), + widths=c(10,35,45,15), + heights=c(30,30,15,15)) + couleurs <- rainbow(75)[1:50]#(50) + ticks <- pretty(coeff) + par(mar=c(1,1,3,1)) + plot(aic,k:1-.5,type='o',pch=21,bg='blue',cex=2,axes=F,lty=2,xpd=NA) + points(aic[choix],k-choix+.5,pch=21,cex=4,bg=2,xpd=NA) + title('aic',line=2) + par(mar=c(3,0,0,0)) + plot(0,axes=F,xlab='',ylab='',xlim=range(ticks),ylim=c(.1,1)) + rect(xleft = min(ticks) + (0:49)/50*(max(ticks)-min(ticks)), + xright = min(ticks) + (1:50)/50*(max(ticks)-min(ticks)), + ytop = rep(1,50), + ybottom= rep(0,50),col=couleurs,border=NA) + axis(1,ticks) + rect(xleft=min(ticks),xright=max(ticks),ytop=1,ybottom=0) + text(mean(coeff,na.rm=T),.5,'coefficients',cex=2,font=2) + par(mar=c(1,1,3,1)) + image(1:n,1:k,t(coeff[k:1,]),axes=F,col=couleurs,zlim=range(ticks)) + for(i in 1:n) for(j in 1:k) if(!is.na(coeff[j,i])) { + if(pval[j,i]<.01) symb = 'green' + else if( (pval[j,i]<.05) & (pval[j,i]>=.01)) symb = 'orange' + else if( (pval[j,i]<.1) & (pval[j,i]>=.05)) symb = 'red' + else symb = 'black' + polygon(c(i+.5 ,i+.2 ,i+.5 ,i+.5), + c(k-j+0.5,k-j+0.5,k-j+0.8,k-j+0.5), + col=symb) + if(j==choix) { + rect(xleft=i-.5, + xright=i+.5, + ybottom=k-j+1.5, + ytop=k-j+.5, + lwd=4) + text(i, + k-j+1, + round(coeff[j,i],2), + cex=1.2, + font=2) + } + else{ + rect(xleft=i-.5,xright=i+.5,ybottom=k-j+1.5,ytop=k-j+.5) + text(i,k-j+1,round(coeff[j,i],2),cex=1.2,font=1) + } + } + axis(3,1:n,noms) + par(mar=c(0.5,0,0,0.5)) + plot(0,axes=F,xlab='',ylab='',type='n',xlim=c(0,8),ylim=c(-.2,.8)) + cols <- c('green','orange','red','black') + niv <- c('0','0.01','0.05','0.1') + for(i in 0:3){ + polygon(c(1+2*i ,1+2*i ,1+2*i-.5 ,1+2*i), + c(.4 ,.7 , .4 , .4), + col=cols[i+1]) + text(2*i,0.5,niv[i+1],cex=1.5) + } + text(8,.5,1,cex=1.5) + text(4,0,'p-value',cex=2) + box() + residus <- arimaSelect.out[[3]][[choix]]$res + par(mar=c(1,2,4,1)) + acf(residus,main='') + title('acf',line=.5) + par(mar=c(1,2,4,1)) + pacf(residus,main='') + title('pacf',line=.5) + par(mar=c(2,2,4,1)) + qqnorm(residus,main='') + title('qq-norm',line=.5) + qqline(residus) + residus + } > if (par2 == 0) x <- log(x) > if (par2 != 0) x <- x^par2 > (selection <- arimaSelect(x, order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5))) [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.07536354 0.3579767 0.5595941 -0.05335312 0.1952286 -0.2930716 [2,] 0.04201336 0.3719312 0.5783005 0.00000000 0.2006072 -0.2985139 [3,] 0.00000000 0.3849650 0.6055371 0.00000000 0.1774517 -0.2939387 [4,] 0.00000000 0.3633936 0.6224611 0.00000000 0.0000000 -0.3213416 [5,] NA NA NA NA NA NA [6,] NA NA NA NA NA NA [7,] NA NA NA NA NA NA [8,] NA NA NA NA NA NA [9,] NA NA NA NA NA NA [10,] NA NA NA NA NA NA [11,] NA NA NA NA NA NA [12,] NA NA NA NA NA NA [13,] NA NA NA NA NA NA [14,] NA NA NA NA NA NA [,7] [1,] -0.8181643 [2,] -0.8182018 [3,] -0.7970721 [4,] -0.6986511 [5,] NA [6,] NA [7,] NA [8,] NA [9,] NA [10,] NA [11,] NA [12,] NA [13,] NA [14,] NA [[2]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0.55338 0 0 0.73569 0.09288 0.00267 0 [2,] 0.57458 0 0 NA 0.07877 0.00190 0 [3,] NA 0 0 NA 0.09786 0.00222 0 [4,] NA 0 0 NA NA 0.00048 0 [5,] NA NA NA NA NA NA NA [6,] NA NA NA NA NA NA NA [7,] NA NA NA NA NA NA NA [8,] NA NA NA NA NA NA NA [9,] NA NA NA NA NA NA NA [10,] NA NA NA NA NA NA NA [11,] NA NA NA NA NA NA NA [12,] NA NA NA NA NA NA NA [13,] NA NA NA NA NA NA NA [14,] NA NA NA NA NA NA NA [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 0.0754 0.3580 0.5596 -0.0534 0.1952 -0.2931 -0.8182 s.e. 0.1269 0.0744 0.0963 0.1578 0.1154 0.0959 0.1176 sigma^2 estimated as 0.001986: log likelihood = 234.76, aic = -453.53 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 0.0754 0.3580 0.5596 -0.0534 0.1952 -0.2931 -0.8182 s.e. 0.1269 0.0744 0.0963 0.1578 0.1154 0.0959 0.1176 sigma^2 estimated as 0.001986: log likelihood = 234.76, aic = -453.53 [[3]][[3]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, fixed = last.arma$next.vector, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 0.0420 0.3719 0.5783 0 0.2006 -0.2985 -0.8182 s.e. 0.0747 0.0609 0.0740 0 0.1133 0.0944 0.1171 sigma^2 estimated as 0.001986: log likelihood = 234.7, aic = -455.41 [[3]][[4]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, fixed = last.arma$next.vector, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 0 0.3850 0.6055 0 0.1775 -0.2939 -0.7971 s.e. 0 0.0562 0.0555 0 0.1065 0.0944 0.1059 sigma^2 estimated as 0.002003: log likelihood = 234.54, aic = -457.09 [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL $aic [1] -453.5256 -455.4100 -457.0892 -456.2646 Warning messages: 1: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE 2: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE > postscript(file="/var/www/html/rcomp/tmp/1mhmr1229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > resid <- arimaSelectplot(selection) > dev.off() null device 1 > resid Time Series: Start = 1 End = 156 Frequency = 1 [1] 0.0036908428 0.0037077053 0.0038597555 0.0036845385 0.0037338343 [6] 0.0037906504 0.0035157287 0.0036007672 0.0037340889 0.0037687928 [11] 0.0037955734 0.0036362663 0.0075370686 0.0164106682 -0.0385071919 [16] 0.0221469779 0.0392775770 0.0004609583 0.0548314663 -0.0255955376 [21] 0.0036258881 0.0105554832 -0.0723130847 0.0304809449 0.0252717727 [26] 0.0331675063 -0.0488523670 0.0738710263 -0.0087248751 0.0182608071 [31] 0.0099816411 -0.0295121817 -0.0062544608 0.0144092649 0.0260321155 [36] 0.0698834255 -0.0172700610 0.0170059735 -0.0016202482 0.0226616217 [41] -0.0348401027 0.0316268992 0.1031658182 0.0567613445 -0.0012549718 [46] -0.0768300117 -0.0261685216 -0.0163534034 -0.0611862795 -0.0507009305 [51] 0.0372005142 0.0337310344 -0.0216069054 0.0236312584 0.0188245582 [56] 0.0541748811 0.0189142613 -0.0008341981 0.0167288976 0.0982574064 [61] 0.0108219599 0.0525253804 0.0460315420 -0.0762480239 0.0687725742 [66] -0.0762887793 0.0238268149 0.0199426147 0.0180317211 -0.0404951434 [71] 0.0534760315 0.0178936202 0.0611967620 -0.0723292169 -0.0404046875 [76] -0.0588907177 -0.0130989527 -0.0445612038 -0.0259945447 -0.0150327775 [81] -0.0508976448 -0.0170539812 0.0024797601 -0.0348891414 -0.0121270702 [86] 0.0144667043 -0.0054222352 0.0405972263 0.0751815008 -0.0134155250 [91] 0.0498424165 0.0034958365 0.0066083173 0.0271206071 0.0120257542 [96] 0.0569785576 0.0548373015 -0.0247221029 -0.0968368486 -0.0242793798 [101] -0.0304128263 -0.0273620181 0.0569891682 -0.0199379497 0.0006930010 [106] 0.0286949689 -0.0010589879 0.0077199703 -0.0085202880 0.0189111459 [111] 0.0584303565 0.0359802925 -0.0940614046 0.0925408011 0.0349951709 [116] 0.0586048203 -0.0388319162 -0.0580075162 0.0003979246 0.0735639760 [121] -0.0026091298 -0.0685000059 -0.0928793782 0.0167298446 0.0167356455 [126] 0.0192114320 -0.0580629893 0.0157759346 0.0347748173 -0.0653724761 [131] 0.0525974687 0.0980557093 0.0554356674 -0.0940491202 0.0352454313 [136] -0.0746960943 0.0195465999 -0.0099184333 0.0224416934 0.0049395124 [141] 0.0118918410 0.0483296241 0.0159647767 -0.0798388713 0.0025837091 [146] 0.0108124722 -0.0033703816 -0.0702647871 0.0435914691 0.0456842100 [151] 0.0928813959 0.0186220871 -0.0756744317 -0.0122476270 0.0312025646 [156] -0.0204031762 > postscript(file="/var/www/html/rcomp/tmp/2z2vp1229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(resid,length(resid)/2, main='Residual Autocorrelation Function') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3oans1229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(resid,length(resid)/2, main='Residual Partial Autocorrelation Function') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4bs7d1229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > cpgram(resid, main='Residual Cumulative Periodogram') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5qzbx1229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(resid, main='Residual Histogram', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/6kc371229249830.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/7ot8h1229249831.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(resid, main='Residual Normal Q-Q Plot') > qqline(resid) > dev.off() null device 1 > ncols <- length(selection[[1]][1,]) > nrows <- length(selection[[2]][,1])-1 > > #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,'ARIMA Parameter Estimation and Backward Selection', ncols+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Iteration', header=TRUE) > for (i in 1:ncols) { + a<-table.element(a,names(selection[[3]][[1]]$coef)[i],header=TRUE) + } > a<-table.row.end(a) > for (j in 1:nrows) { + a<-table.row.start(a) + mydum <- 'Estimates (' + mydum <- paste(mydum,j) + mydum <- paste(mydum,')') + a<-table.element(a,mydum, header=TRUE) + for (i in 1:ncols) { + a<-table.element(a,round(selection[[1]][j,i],4)) + } + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'(p-val)', header=TRUE) + for (i in 1:ncols) { + mydum <- '(' + mydum <- paste(mydum,round(selection[[2]][j,i],4),sep='') + mydum <- paste(mydum,')') + a<-table.element(a,mydum) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/85dxy1229249831.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimated ARIMA Residuals', 1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Value', 1,TRUE) > a<-table.row.end(a) > for (i in (par4*par5+par3):length(resid)) { + a<-table.row.start(a) + a<-table.element(a,resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/9yt551229249831.tab") > > system("convert tmp/1mhmr1229249830.ps tmp/1mhmr1229249830.png") > system("convert tmp/2z2vp1229249830.ps tmp/2z2vp1229249830.png") > system("convert tmp/3oans1229249830.ps tmp/3oans1229249830.png") > system("convert tmp/4bs7d1229249830.ps tmp/4bs7d1229249830.png") > system("convert tmp/5qzbx1229249830.ps tmp/5qzbx1229249830.png") > system("convert tmp/6kc371229249830.ps tmp/6kc371229249830.png") > system("convert tmp/7ot8h1229249831.ps tmp/7ot8h1229249831.png") > > > proc.time() user system elapsed 11.258 1.599 16.655