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Type 'q()' to quit R. > x <- c(26.663 + ,23.598 + ,26.931 + ,24.740 + ,25.806 + ,24.364 + ,24.477 + ,23.901 + ,23.175 + ,23.227 + ,21.672 + ,21.870 + ,21.439 + ,21.089 + ,23.709 + ,21.669 + ,21.752 + ,20.761 + ,23.479 + ,23.824 + ,23.105 + ,23.110 + ,21.759 + ,22.073 + ,21.937 + ,20.035 + ,23.590 + ,21.672 + ,22.222 + ,22.123 + ,23.950 + ,23.504 + ,22.238 + ,23.142 + ,21.059 + ,21.573 + ,21.548 + ,20.000 + ,22.424 + ,20.615 + ,21.761 + ,22.874 + ,24.104 + ,23.748 + ,23.262 + ,22.907 + ,21.519 + ,22.025 + ,22.604 + ,20.894 + ,24.677 + ,23.673 + ,25.320 + ,23.583 + ,24.671 + ,24.454 + ,24.122 + ,24.252 + ,22.084 + ,22.991 + ,23.287 + ,23.049 + ,25.076 + ,24.037 + ,24.430 + ,24.667 + ,26.451 + ,25.618 + ,25.014 + ,25.110 + ,22.964 + ,23.981 + ,23.798 + ,22.270 + ,24.775 + ,22.646 + ,23.988 + ,24.737 + ,26.276 + ,25.816 + ,25.210 + ,25.199 + ,23.162 + ,24.707 + ,24.364 + ,22.644 + ,25.565 + ,24.062 + ,25.431 + ,24.635 + ,27.009 + ,26.606 + ,26.268 + ,26.462 + ,25.246 + ,25.180 + ,24.657 + ,23.304 + ,26.982 + ,26.199 + ,27.210 + ,26.122 + ,26.706 + ,26.878 + ,26.152 + ,26.379 + ,24.712 + ,25.688 + ,24.990 + ,24.239 + ,26.721 + ,23.475 + ,24.767 + ,26.219 + ,28.361 + ,28.599 + ,27.914 + ,27.784 + ,25.693 + ,26.881 + ,26.217 + ,24.218 + ,27.914 + ,26.975 + ,28.527 + ,27.139 + ,28.982 + ,28.169 + ,28.056 + ,29.136 + ,26.291 + ,26.987 + ,26.589 + ,24.848 + ,27.543 + ,26.896 + ,28.878 + ,27.390 + ,28.065 + ,28.141 + ,29.048 + ,28.484 + ,26.634 + ,27.735 + ,27.132 + ,24.924 + ,28.963 + ,26.589 + ,27.931 + ,28.009 + ,29.229 + ,28.759 + ,28.405 + ,27.945 + ,25.912 + ,26.619 + ,26.076 + ,25.286 + ,27.660 + ,25.951 + ,26.398 + ,25.565 + ,28.865 + ,30.000 + ,29.261 + ,29.012 + ,26.992 + ,27.897) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > if (par1 == 'TRUE') par1 <- TRUE > if (par1 == 'FALSE') par1 <- FALSE > par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial > par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial > par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial > par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial > armaGR <- function(arima.out, names, n){ + try1 <- arima.out$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,] -0.03316941 -0.2054032 -0.1736467 -0.04663290 -0.4298956 -0.2888167 [2,] 0.00000000 -0.2044883 -0.1664840 -0.07991384 -0.4289099 -0.2868784 [3,] 0.00000000 -0.2060004 -0.1639952 0.00000000 -0.4335878 -0.2836310 [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,] -0.6628410 [2,] -0.6637130 [3,] -0.6686616 [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,] 0.94708 0.01266 0.18947 0.92691 0.00045 0.01201 0 [2,] NA 0.01193 0.03876 0.33701 0.00041 0.00971 0 [3,] NA 0.01115 0.04220 NA 0.00036 0.01091 0 [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 -0.0332 -0.2054 -0.1736 -0.0466 -0.4299 -0.2888 -0.6628 s.e. 0.4989 0.0815 0.1318 0.5076 0.1201 0.1137 0.1179 sigma^2 estimated as 0.3817: log likelihood = -154.75, aic = 325.5 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 -0.0332 -0.2054 -0.1736 -0.0466 -0.4299 -0.2888 -0.6628 s.e. 0.4989 0.0815 0.1318 0.5076 0.1201 0.1137 0.1179 sigma^2 estimated as 0.3817: log likelihood = -154.75, aic = 325.5 [[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 -0.2045 -0.1665 -0.0799 -0.4289 -0.2869 -0.6637 s.e. 0 0.0804 0.0799 0.0830 0.1190 0.1096 0.1170 sigma^2 estimated as 0.3817: log likelihood = -154.75, aic = 323.5 [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL $aic [1] 325.4976 323.5021 322.4283 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/wessaorg/rcomp/tmp/1urmr1322836182.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 = 168 Frequency = 1 [1] 0.0153938838 0.0045102094 0.0057695199 0.0023680649 0.0028532931 [6] 0.0010476329 0.0010023339 0.0003354571 -0.0003886636 -0.0003002323 [11] -0.0017587325 -0.0157767553 -0.1044320812 1.7187473204 -0.3929278128 [16] 0.4359718154 -0.4103971602 0.1940287963 1.5971850685 0.7028997789 [21] 0.5134694155 0.4578004330 0.1277300773 -0.0628305670 0.1551521867 [26] -0.0400106673 0.4369108494 0.2130747203 0.0366277434 1.0040431080 [31] 0.5226053841 0.0051554416 -0.1468452304 0.7470036029 -0.6602949814 [36] 0.0949063118 0.1667670728 0.3494712861 -0.5898661440 0.3369585455 [41] 0.4077240131 2.0123960463 0.2905104902 0.4275277651 0.6937837952 [46] -0.4313312530 0.1176471644 0.1076088800 0.7224129426 -0.0933287734 [51] 0.8798347728 1.1721132071 1.3385394987 -0.3630835505 -0.2664465682 [56] -0.0970605611 0.2426248325 -0.1860717415 -0.5328215300 0.5472173618 [61] 0.3555849206 1.3941349049 -0.7375072122 1.2808206340 -0.0183078342 [66] 0.6075299242 0.2360289217 -0.4733894789 0.4145080353 -0.3124222301 [71] -0.5538589363 0.5701953978 -0.2344421504 0.2077396400 -0.4644402248 [76] -0.2471374268 0.3600307225 0.8049759392 0.1673919005 0.0424588230 [81] 0.3163403370 -0.1503984861 -0.4524990148 1.0424974280 -0.5608067404 [86] -0.0953490799 -0.1839945999 -0.1443727818 0.2829212875 -0.1737791334 [91] 1.0211729187 -0.0015797072 0.4580990228 0.2324227120 0.6458576277 [96] -0.5257787971 -0.6481627386 -0.3014722117 0.6274354081 0.5580261654 [101] 0.3701582609 -0.5908141163 -0.7659425926 0.4120850639 -0.3785179517 [106] 0.0840043868 0.4158414180 0.1260862497 -0.6878448778 0.5748996884 [111] -0.2511593173 -1.5626475798 0.1895173454 1.0458844144 0.3356353742 [116] 1.0947856661 0.3048979496 0.0547661256 -0.0615091476 0.1870884519 [121] -0.6653547617 -0.5430977632 0.6914325302 0.2927460170 0.5501812134 [126] -0.6555927467 0.2698889885 -0.4564358641 0.2510767946 0.9069955472 [131] -1.0811911130 0.2364254571 -0.2423544182 -0.6471898490 -0.3573789282 [136] 0.7208550586 0.8434403303 -1.0056663451 -0.4928257113 0.0836033372 [141] 1.2026794110 -0.5906283075 0.0744774456 0.4365744103 -0.3114878771 [146] -1.0122055106 1.0049673158 -0.5218355524 0.2381529114 0.0333136886 [151] -0.5471780222 -0.3468774521 0.2159750187 -0.7947541133 -0.1677446661 [156] -0.2507694902 -0.2381983805 0.5480646140 -0.6615102711 -0.1722595466 [161] -0.9404257223 -0.5610703701 1.3563127589 1.3040490031 -0.0072906062 [166] -0.0936394093 0.2844717287 -0.1392025323 > postscript(file="/var/wessaorg/rcomp/tmp/2z1ch1322836182.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/wessaorg/rcomp/tmp/3hrxr1322836182.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/wessaorg/rcomp/tmp/4ezub1322836182.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/wessaorg/rcomp/tmp/53oup1322836182.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/wessaorg/rcomp/tmp/6rk7v1322836182.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/wessaorg/rcomp/tmp/762zh1322836182.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/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,'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/wessaorg/rcomp/tmp/8xaer1322836182.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/wessaorg/rcomp/tmp/920j21322836182.tab") > > try(system("convert tmp/1urmr1322836182.ps tmp/1urmr1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/2z1ch1322836182.ps tmp/2z1ch1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/3hrxr1322836182.ps tmp/3hrxr1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/4ezub1322836182.ps tmp/4ezub1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/53oup1322836182.ps tmp/53oup1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/6rk7v1322836182.ps tmp/6rk7v1322836182.png",intern=TRUE)) character(0) > try(system("convert tmp/762zh1322836182.ps tmp/762zh1322836182.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.844 0.771 8.665