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Type 'q()' to quit R. > x <- c(206010 + ,198112 + ,194519 + ,185705 + ,180173 + ,176142 + ,203401 + ,221902 + ,197378 + ,185001 + ,176356 + ,180449 + ,180144 + ,173666 + ,165688 + ,161570 + ,156145 + ,153730 + ,182698 + ,200765 + ,176512 + ,166618 + ,158644 + ,159585 + ,163095 + ,159044 + ,155511 + ,153745 + ,150569 + ,150605 + ,179612 + ,194690 + ,189917 + ,184128 + ,175335 + ,179566 + ,181140 + ,177876 + ,175041 + ,169292 + ,166070 + ,166972 + ,206348 + ,215706 + ,202108 + ,195411 + ,193111 + ,195198 + ,198770 + ,194163 + ,190420 + ,189733 + ,186029 + ,191531 + ,232571 + ,243477 + ,227247 + ,217859 + ,208679 + ,213188 + ,216234 + ,213586 + ,209465 + ,204045 + ,200237 + ,203666 + ,241476 + ,260307 + ,243324 + ,244460 + ,233575 + ,237217 + ,235243 + ,230354 + ,227184 + ,221678 + ,217142 + ,219452 + ,256446 + ,265845 + ,248624 + ,241114 + ,229245 + ,231805 + ,219277 + ,219313 + ,212610 + ,214771 + ,211142 + ,211457 + ,240048 + ,240636 + ,230580 + ,208795 + ,197922 + ,194596 + ,194581 + ,185686 + ,178106 + ,172608 + ,167302 + ,168053 + ,202300 + ,202388 + ,182516 + ,173476 + ,166444 + ,171297 + ,169701 + ,164182 + ,161914 + ,159612 + ,151001 + ,158114 + ,186530 + ,187069 + ,174330 + ,169362 + ,166827 + ,178037 + ,186413 + ,189226 + ,191563 + ,188906 + ,186005 + ,195309 + ,223532 + ,226899 + ,214126 + ,206903 + ,204442 + ,220375 + ,214320 + ,212588 + ,205816 + ,202196 + ,195722 + ,198563 + ,229139 + ,229527 + ,211868 + ,203555 + ,195770) > par9 = '0' > par8 = '2' > par7 = '1' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '1' > par2 = '1' > 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,] 0.7684903 0.2713182 -0.1251859 -0.7896107 -0.4574416 -0.2800851 [2,] 0.6566984 0.2148080 0.0000000 -0.6968546 -0.4391959 -0.2778333 [3,] NA NA NA NA NA NA [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 [[2]] [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.00000 0.01293 0.23748 0e+00 0 0.00227 [2,] 0.00022 0.03156 NA 4e-05 0 0.00241 [3,] NA NA NA NA NA NA [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 [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 0.7685 0.2713 -0.1252 -0.7896 -0.4574 -0.2801 s.e. 0.1480 0.1077 0.1055 0.1148 0.0899 0.0900 sigma^2 estimated as 20996477: log likelihood = -1282.16, aic = 2578.33 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 0.7685 0.2713 -0.1252 -0.7896 -0.4574 -0.2801 s.e. 0.1480 0.1077 0.1055 0.1148 0.0899 0.0900 sigma^2 estimated as 20996477: log likelihood = -1282.16, aic = 2578.33 [[3]][[3]] NULL [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL $aic [1] 2578.329 2577.746 Warning message: 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/1nkje1293187875.ps",horizontal=F,onefile=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 = 143 Frequency = 1 [1] 1.189399e+02 4.707374e+01 2.778030e+01 1.293295e+01 5.312998e+00 [6] 7.126702e-01 2.598696e+01 4.010342e+01 1.243527e+01 -5.845071e-01 [11] -8.791831e+00 -1.159216e+02 -7.699129e+02 1.231747e+03 -3.786512e+03 [16] 3.857063e+03 1.137677e+03 6.505593e+02 1.448387e+03 -7.855497e+02 [21] -3.204048e+02 2.132006e+03 4.272257e+02 -3.403282e+03 2.733996e+03 [26] 3.258621e+03 2.037743e+03 2.990713e+03 1.208251e+03 1.494875e+03 [31] -5.197407e+02 -4.402275e+03 1.787198e+04 5.459444e+03 -5.409314e+03 [36] -5.632092e+02 -2.049067e+03 3.892254e+02 4.555207e+02 -3.060668e+03 [41] -2.980578e+02 2.045440e+03 1.012785e+04 -8.097878e+03 -3.333403e+03 [46] 2.225009e+03 5.836709e+03 -2.191136e+03 1.177961e+02 -6.838594e+02 [51] -4.329108e+02 3.407879e+03 -3.944290e+02 4.298032e+03 5.898496e+03 [56] -3.706422e+03 -3.704920e+03 -2.629454e+03 -4.621331e+03 2.273655e+03 [61] 7.034010e+02 1.079833e+03 -6.103230e+02 -3.999428e+03 -4.221422e+02 [66] 1.083450e+03 7.297396e+02 7.156137e+03 -4.265310e+03 7.221072e+03 [71] -2.196147e+03 -2.769165e+03 -4.656643e+03 -2.067489e+03 1.444305e+03 [76] -2.169072e+02 -7.990358e+02 -4.183914e+02 -1.416535e+03 -4.989984e+03 [81] -7.322046e+02 -2.920548e+03 -2.787642e+03 9.140070e+02 -1.123363e+04 [86] 5.322022e+03 1.006134e+03 6.724495e+03 2.437705e+03 -3.692298e+03 [91] -9.582622e+03 -1.012684e+04 9.470162e+03 -1.131812e+04 -3.466786e+02 [96] -1.946714e+03 7.900621e+03 -4.087103e+03 -2.372434e+03 -1.569675e+03 [101] 1.932781e+02 1.343444e+03 3.126474e+03 -5.889719e+03 -6.272397e+03 [106] 6.060814e+03 6.785709e+03 5.595325e+03 1.005556e+03 -3.511425e+02 [111] 3.455976e+03 1.522078e+03 -5.010204e+03 4.972431e+03 -5.017735e+03 [116] -4.012769e+03 5.476812e+03 6.563843e+03 5.636183e+03 6.859908e+03 [121] 1.064309e+04 4.503092e+03 2.275004e+03 -4.863713e+03 -2.329774e+02 [126] 3.305722e+03 -3.821613e+03 -9.303378e+01 -8.179168e+02 1.217945e+03 [131] 1.959025e+03 8.202109e+03 -1.193285e+04 -3.576002e+03 -4.461261e+03 [136] -8.633827e+02 -8.687229e+02 -3.542784e+03 1.144344e+03 -3.788305e+02 [141] -2.636617e+03 -3.294002e+02 -2.944138e+03 > postscript(file="/var/www/html/rcomp/tmp/2xt0z1293187875.ps",horizontal=F,onefile=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/3xt0z1293187875.ps",horizontal=F,onefile=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/4xt0z1293187875.ps",horizontal=F,onefile=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/5xt0z1293187875.ps",horizontal=F,onefile=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/682h21293187875.ps",horizontal=F,onefile=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/782h21293187875.ps",horizontal=F,onefile=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/84cfs1293187875.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/97dzq1293187876.tab") > > try(system("convert tmp/1nkje1293187875.ps tmp/1nkje1293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/2xt0z1293187875.ps tmp/2xt0z1293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/3xt0z1293187875.ps tmp/3xt0z1293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/4xt0z1293187875.ps tmp/4xt0z1293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/5xt0z1293187875.ps tmp/5xt0z1293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/682h21293187875.ps tmp/682h21293187875.png",intern=TRUE)) character(0) > try(system("convert tmp/782h21293187875.ps tmp/782h21293187875.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.256 1.267 13.364