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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 = '1' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > if (par1 == 'TRUE') par1 <- TRUE > if (par1 == 'FALSE') par1 <- FALSE > par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial > par7 <- 3 > par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial > par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial > armaGR <- function(arima.out, names, n){ + try1 <- arima.out$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] [,7] [1,] -0.7890897 0.7064554 0.7695321 0.8122546 -0.4844510 -0.5933278 0.03225341 [2,] -0.8575809 0.8112913 0.7200726 0.9112632 -0.6111207 -0.5223807 0.00000000 [3,] -0.9088480 0.6781384 0.9103130 1.0258878 -0.4375456 -0.7887431 0.00000000 [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 [15,] NA NA NA NA NA NA NA [16,] NA NA NA NA NA NA NA [17,] NA NA NA NA NA NA NA [18,] NA NA NA NA NA NA NA [,8] [,9] [1,] -0.1202309 -0.5329431 [2,] -0.1584842 -0.4932258 [3,] 0.0000000 -0.5393190 [4,] NA NA [5,] NA NA [6,] NA NA [7,] NA NA [8,] NA NA [9,] NA NA [10,] NA NA [11,] NA NA [12,] NA NA [13,] NA NA [14,] NA NA [15,] NA NA [16,] NA NA [17,] NA NA [18,] NA NA [[2]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [1,] 1e-04 0 0.00046 0.00160 0.00957 0.02851 0.88711 0.37654 0.01583 [2,] 3e-05 0 0.00011 0.00041 0.00089 0.02815 NA 0.13084 0.00000 [3,] 0e+00 0 0.00000 0.00000 0.01425 0.00000 NA NA 0.00000 [4,] NA NA NA NA NA NA NA NA NA [5,] NA NA NA NA NA NA NA NA NA [6,] NA NA NA NA NA NA NA NA NA [7,] NA NA NA NA NA NA NA NA NA [8,] NA NA NA NA NA NA NA NA NA [9,] NA NA NA NA NA NA NA NA NA [10,] NA NA NA NA NA NA NA NA NA [11,] NA NA NA NA NA NA NA NA NA [12,] NA NA NA NA NA NA NA NA NA [13,] NA NA NA NA NA NA NA NA NA [14,] NA NA NA NA NA NA NA NA NA [15,] NA NA NA NA NA NA NA NA NA [16,] NA NA NA NA NA NA NA NA NA [17,] NA NA NA NA NA NA NA NA NA [18,] NA NA 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 ma2 ma3 sar1 sar2 -0.7891 0.7065 0.7695 0.8123 -0.4845 -0.5933 0.0323 -0.1202 s.e. 0.1971 0.1416 0.2140 0.2521 0.1843 0.2680 0.2268 0.1355 sma1 -0.5329 s.e. 0.2180 sigma^2 estimated as 19970285: log likelihood = -1279.63, aic = 2579.25 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 ma2 ma3 sar1 sar2 -0.7891 0.7065 0.7695 0.8123 -0.4845 -0.5933 0.0323 -0.1202 s.e. 0.1971 0.1416 0.2140 0.2521 0.1843 0.2680 0.2268 0.1355 sma1 -0.5329 s.e. 0.2180 sigma^2 estimated as 19970285: log likelihood = -1279.63, aic = 2579.25 [[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 ma2 ma3 sar1 sar2 sma1 -0.8576 0.8113 0.7201 0.9113 -0.6111 -0.5224 0 -0.1585 -0.4932 s.e. 0.1979 0.1316 0.1805 0.2516 0.1798 0.2354 0 0.1043 0.0928 sigma^2 estimated as 19088397: log likelihood = -1278.54, aic = 2575.08 [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL [[3]][[8]] NULL [[3]][[9]] NULL $aic [1] 2579.253 2575.077 2576.419 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/1g6he1292770711.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 5.312995e+00 [6] 7.126690e-01 2.598696e+01 4.010341e+01 1.243526e+01 -5.845177e-01 [11] -8.791838e+00 -1.159216e+02 -7.699111e+02 1.171294e+03 -3.576199e+03 [16] 3.609026e+03 1.095799e+03 4.935710e+02 1.699038e+03 -8.368518e+02 [21] -2.733327e+02 2.168446e+03 1.262805e+02 -2.912499e+03 2.528279e+03 [26] 3.062627e+03 1.838544e+03 3.170783e+03 1.031288e+03 1.693885e+03 [31] -5.349313e+02 -3.998679e+03 1.697649e+04 4.820762e+03 -4.679060e+03 [36] 5.977390e+02 -2.477863e+03 2.435002e+02 5.388586e+02 -3.200237e+03 [41] 3.243805e+02 1.527488e+03 1.015201e+04 -8.059362e+03 -2.418700e+03 [46] 1.731698e+03 5.707521e+03 -2.457741e+03 1.308431e+03 -1.090405e+03 [51] 2.393267e+02 3.112882e+03 7.353410e+02 3.676497e+03 7.161953e+03 [56] -5.271524e+03 -6.154909e+02 -2.953674e+03 -3.959282e+03 9.600065e+02 [61] 1.416518e+03 6.348246e+02 7.203975e+02 -4.470204e+03 7.121740e+02 [66] 6.327144e+02 2.421352e+03 5.025051e+03 -1.844601e+03 7.934365e+03 [71] -2.477425e+03 -2.659077e+03 -4.568252e+03 -2.153241e+03 1.086694e+03 [76] -3.481220e+02 -1.194074e+03 9.755918e+02 -1.339596e+02 -5.399055e+03 [81] -2.095610e+03 -2.266495e+03 -3.160810e+03 1.344928e+03 -1.195505e+04 [86] 6.424591e+03 -7.658134e+02 7.754340e+03 1.287979e+03 -1.575274e+03 [91] -9.483766e+03 -8.373247e+03 6.676871e+03 -1.040282e+04 -1.759943e+03 [96] -1.095855e+03 5.697048e+03 -3.295264e+03 -2.174629e+03 -1.673195e+03 [101] 5.122734e+01 8.942074e+02 3.271208e+03 -6.741806e+03 -4.763838e+03 [106] 5.149959e+03 6.359493e+03 4.069354e+03 8.614633e+02 -1.076125e+03 [111] 4.778747e+03 6.600113e+02 -3.644177e+03 4.021367e+03 -5.651227e+03 [116] -6.165268e+03 6.483381e+03 3.857600e+03 6.052523e+03 6.726939e+03 [121] 1.009737e+04 4.513374e+03 2.970101e+03 -4.046520e+03 6.361052e+02 [126] 2.404078e+03 -4.585667e+03 -2.297290e+03 2.313914e+02 -2.145776e+02 [131] 3.258093e+03 8.146929e+03 -1.015409e+04 -2.913353e+03 -4.751016e+03 [136] -1.109699e+03 -1.853912e+03 -2.165278e+03 2.943754e+02 -9.381312e+02 [141] -3.698263e+03 2.449850e+03 -2.776863e+03 > postscript(file="/var/www/html/rcomp/tmp/2g6he1292770711.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/3g6he1292770711.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/4qxgh1292770711.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/5qxgh1292770711.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/6qxgh1292770711.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/7qxgh1292770711.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/8m7e71292770711.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/9fzda1292770711.tab") > try(system("convert tmp/1g6he1292770711.ps tmp/1g6he1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/2g6he1292770711.ps tmp/2g6he1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/3g6he1292770711.ps tmp/3g6he1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/4qxgh1292770711.ps tmp/4qxgh1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/5qxgh1292770711.ps tmp/5qxgh1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/6qxgh1292770711.ps tmp/6qxgh1292770711.png",intern=TRUE)) character(0) > try(system("convert tmp/7qxgh1292770711.ps tmp/7qxgh1292770711.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 26.181 2.936 69.173