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Type 'q()' to quit R. > x <- c(0.24,0.23,0.23,0.24,0.23,0.23,0.25,0.21,0.26,0.25,0.24,0.24,0.27,0.25,0.26,0.29,0.24,0.26,0.24,0.26,0.25,0.26,0.24,0.21,0.20,0.22,0.20,0.21,0.20,0.19,0.20,0.20,0.21,0.24,0.22,0.19,0.23,0.23,0.23,0.22,0.23,0.25,0.25,0.22,0.25,0.25,0.24,0.19,0.24,0.26,0.24,0.24,0.25,0.23,0.27,0.24,0.26,0.27,0.29,0.28,0.32,0.29,0.27,0.26,0.28,0.31,0.29,0.31,0.31,0.32,0.32,0.26,0.31,0.31,0.31,0.31,0.29,0.27,0.30,0.27,0.27,0.30,0.28,0.24,0.28,0.28,0.33,0.28,0.29,0.25,0.31,0.29,0.37,0.31,0.29,0.28,0.30,0.32,0.31,0.28,0.29,0.29,0.28,0.26,0.28,0.30,0.33,0.31,0.37,0.36,0.37,0.37,0.36,0.33,0.33,0.40,0.32,0.39,0.39,0.37,0.37,0.30,0.33,0.33,0.34,0.35,0.34,0.37,0.37,0.37,0.36,0.32,0.33,0.35,0.36,0.35,0.37,0.35,0.32,0.33,0.28,0.32,0.35,0.30,0.32,0.32,0.32,0.32,0.36,0.31,0.26,0.33,0.31,0.34,0.33,0.38,0.32,0.30,0.32,0.33,0.34,0.29,0.33,0.36,0.32,0.32,0.32,0.31,0.30,0.34,0.34,0.30,0.28,0.25,0.27,0.33,0.28,0.33,0.32,0.27,0.27,0.28,0.27,0.27,0.25,0.25,0.22,0.27) > par9 = '1' > par8 = '2' > par7 = '1' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '2' > par2 = '-0.2' > 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,] -0.4867950 -0.2356398 -0.1973425 -0.996702 -0.3146309 -0.2203917 [2,] -0.5064138 -0.2510810 -0.2077547 -1.003158 -0.1457394 0.0000000 [3,] -0.5036318 -0.2451769 -0.1845221 -1.000702 0.0000000 0.0000000 [4,] NA NA NA NA NA NA [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,] -0.5456310 [2,] -0.7050141 [3,] -0.7696576 [4,] NA [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 0.00496 0.01161 0 0.01901 0.04284 3e-05 [2,] 0 0.00278 0.00715 0 0.13939 NA 0e+00 [3,] 0 0.00347 0.01446 0 NA NA 0e+00 [4,] NA NA NA NA NA NA NA [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 -0.4868 -0.2356 -0.1973 -0.9967 -0.3146 -0.2204 -0.5456 s.e. 0.0768 0.0828 0.0774 0.0612 0.1329 0.1080 0.1267 sigma^2 estimated as 0.0004812: log likelihood = 404.98, aic = -793.97 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 -0.4868 -0.2356 -0.1973 -0.9967 -0.3146 -0.2204 -0.5456 s.e. 0.0768 0.0828 0.0774 0.0612 0.1329 0.1080 0.1267 sigma^2 estimated as 0.0004812: log likelihood = 404.98, aic = -793.97 [[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 -0.5064 -0.2511 -0.2078 -1.0032 -0.1457 0 -0.7050 s.e. 0.0757 0.0828 0.0764 0.0654 0.0982 0 0.0754 sigma^2 estimated as 0.0004894: log likelihood = 403.13, aic = -792.25 [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL $aic [1] -793.9698 -792.2546 -792.1495 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/1prt81228824168.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 = 188 Frequency = 1 [1] 0.0004011080 -0.0003073223 -0.0004146230 -0.0004183603 -0.0003742232 [6] -0.0003416786 -0.0003279579 -0.0002552697 -0.0002881962 -0.0002485429 [11] -0.0007661635 -0.0005665033 -0.0020408852 0.0047538640 -0.0073920335 [16] -0.0100736857 0.0238941435 -0.0082604076 0.0250110855 -0.0361818801 [21] 0.0279304717 -0.0001411225 -0.0027607533 0.0313127345 0.0415924106 [26] -0.0252994083 0.0087233639 0.0013273601 -0.0263318200 0.0086889426 [31] -0.0143008331 -0.0274189178 -0.0012340532 -0.0400978523 -0.0130195002 [36] 0.0156835439 -0.0323912109 -0.0165642191 -0.0097626239 0.0189459384 [41] -0.0252050728 -0.0272796280 -0.0061985449 0.0184797125 -0.0028568962 [46] 0.0110048764 0.0012158092 0.0325451729 -0.0232041993 -0.0315097579 [51] 0.0048523242 0.0079629772 -0.0192230553 0.0219784683 -0.0257852625 [56] 0.0047370904 0.0085073458 0.0015423797 -0.0265452358 -0.0383512497 [61] -0.0160663989 0.0212591642 0.0253797572 0.0326257764 -0.0065975403 [66] -0.0256797303 0.0163415472 -0.0275401309 0.0120540535 0.0147102579 [71] -0.0060012946 0.0223860818 0.0033234940 0.0044394006 -0.0044699923 [76] -0.0000293546 0.0186924209 0.0307283891 0.0010429165 0.0150682181 [81] 0.0267204755 -0.0072295246 0.0128138071 0.0130019032 0.0013483851 [86] 0.0014330006 -0.0513259749 0.0162663711 -0.0003114846 0.0373496390 [91] -0.0184498363 -0.0088055587 -0.0462994100 0.0253046418 0.0298587473 [96] -0.0178547425 0.0229293700 -0.0106528139 -0.0014577620 0.0243320513 [101] -0.0017144195 -0.0045551494 0.0263485768 0.0147022189 0.0068386891 [106] -0.0057641616 -0.0382560116 -0.0370848992 -0.0258141157 -0.0052464310 [111] -0.0021341103 -0.0128905934 0.0044496876 0.0136024161 0.0264594794 [116] -0.0461921173 0.0568035740 -0.0183109484 -0.0210780223 -0.0109365452 [121] 0.0180008312 0.0685934375 0.0126273286 -0.0031310451 -0.0063255840 [126] -0.0274942180 0.0076595347 -0.0220021828 0.0007198053 0.0145527870 [131] 0.0098579423 0.0147849283 0.0302952736 -0.0068838499 -0.0040141787 [136] -0.0031861399 -0.0178429664 -0.0020545048 0.0291589950 0.0115035601 [141] 0.0491546724 0.0066793587 -0.0237970365 0.0073814025 0.0042730826 [146] -0.0083562736 0.0084041046 -0.0048892248 -0.0292692823 0.0166623708 [151] 0.0528576611 -0.0280435975 0.0002421944 -0.0072023468 -0.0040559967 [156] -0.0562322292 0.0320193496 0.0288509782 -0.0007013677 -0.0034498754 [161] -0.0057601612 0.0221988852 -0.0309350317 -0.0198496309 0.0088453276 [166] 0.0171492755 0.0154883700 -0.0013988043 0.0170281138 -0.0307716001 [171] -0.0092260573 0.0258713363 0.0370909676 0.0315910446 -0.0115994229 [176] -0.0346574242 0.0060993003 -0.0251079601 -0.0034056898 0.0369781108 [181] 0.0129787159 -0.0021748335 0.0173554833 -0.0013381368 0.0246026667 [186] -0.0102506154 0.0277851681 -0.0108850684 > postscript(file="/var/www/html/rcomp/tmp/2bous1228824168.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/3adqf1228824168.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/4xbcy1228824168.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/5ukxb1228824168.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/68sge1228824168.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/76qgi1228824168.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/8co1q1228824168.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/9inac1228824168.tab") > > system("convert tmp/1prt81228824168.ps tmp/1prt81228824168.png") > system("convert tmp/2bous1228824168.ps tmp/2bous1228824168.png") > system("convert tmp/3adqf1228824168.ps tmp/3adqf1228824168.png") > system("convert tmp/4xbcy1228824168.ps tmp/4xbcy1228824168.png") > system("convert tmp/5ukxb1228824168.ps tmp/5ukxb1228824168.png") > system("convert tmp/68sge1228824168.ps tmp/68sge1228824168.png") > system("convert tmp/76qgi1228824168.ps tmp/76qgi1228824168.png") > > > proc.time() user system elapsed 9.441 1.521 10.375