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Type 'q()' to quit R. > x <- c(205597 + ,205471 + ,211064 + ,212856 + ,217036 + ,219302 + ,219759 + ,221388 + ,220834 + ,221788 + ,222358 + ,222972 + ,224164 + ,224915 + ,226294 + ,224690 + ,227021 + ,229284 + ,229189 + ,230032 + ,229389 + ,231053 + ,232560 + ,232681 + ,231555 + ,231428 + ,232141 + ,234939 + ,235424 + ,235471 + ,236355 + ,238693 + ,236958 + ,237060 + ,239282 + ,238252 + ,241552 + ,236230 + ,238909 + ,240723 + ,242120 + ,242100 + ,243276 + ,244677 + ,243494 + ,244902 + ,245247 + ,245578 + ,243052 + ,238121 + ,241863 + ,241203 + ,243634 + ,242351 + ,245180 + ,246126 + ,244424 + ,245166 + ,247258 + ,245094 + ,246020 + ,243082 + ,245555 + ,243685 + ,247277 + ,245029 + ,246169 + ,246778 + ,244577 + ,246048 + ,245775 + ,245328 + ,245477 + ,241903 + ,243219 + ,248088 + ,248521 + ,247389 + ,249057 + ,248916 + ,249193 + ,250768 + ,253106 + ,249829 + ,249447 + ,246755 + ,250785 + ,250140 + ,255755 + ,254671 + ,253919 + ,253741 + ,252729 + ,253810 + ,256653 + ,255231 + ,258405 + ,251061 + ,254811 + ,254895 + ,258325 + ,257608 + ,258759 + ,258621 + ,257852 + ,260560 + ,262358 + ,260812 + ,261165 + ,257164 + ,260720 + ,259581 + ,264743 + ,261845 + ,262262 + ,261631 + ,258953 + ,259966 + ,262850 + ,262204 + ,263418 + ,262752 + ,266433 + ,267722 + ,266003 + ,262971 + ,265521 + ,264676 + ,270223 + ,269508 + ,268457 + ,265814 + ,266680 + ,263018 + ,269285 + ,269829 + ,270911 + ,266844 + ,271244 + ,269907 + ,271296 + ,270157 + ,271322 + ,267179 + ,264101 + ,265518 + ,269419 + ,268714 + ,272482 + ,268351 + ,268175 + ,270674 + ,272764 + ,272599 + ,270333 + ,270846 + ,270491 + ,269160 + ,274027 + ,273784 + ,276663 + ,274525 + ,271344 + ,271115 + ,270798 + ,273911 + ,273985 + ,271917 + ,273338 + ,270601 + ,273547 + ,275363 + ,281229 + ,277793 + ,279913 + ,282500 + ,280041 + ,282166 + ,290304 + ,283519 + ,287816 + ,285226 + ,287595 + ,289741 + ,289148 + ,288301 + ,290155 + ,289648 + ,288225 + ,289351 + ,294735 + ,305333) > par9 = '1' > par8 = '2' > par7 = '1' > par6 = '0' > par5 = '12' > par4 = '0' > 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] [1,] -0.2561081 1.114640 -0.1164252 -0.9606401 [2,] -0.2354317 0.984905 0.0000000 -0.8738939 [3,] NA NA NA NA [4,] NA NA NA NA [5,] NA NA NA NA [6,] NA NA NA NA [7,] NA NA NA NA [8,] NA NA NA NA [[2]] [,1] [,2] [,3] [,4] [1,] 0.00395 0 0.22939 0 [2,] 0.00703 0 NA 0 [3,] NA NA NA NA [4,] NA NA NA NA [5,] NA NA NA NA [6,] NA NA NA NA [7,] NA NA NA NA [8,] NA NA NA NA [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ma1 sar1 sar2 sma1 -0.2561 1.1146 -0.1164 -0.9606 s.e. 0.0878 0.0985 0.0965 0.0914 sigma^2 estimated as 4452080: log likelihood = -1741.88, aic = 3493.75 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ma1 sar1 sar2 sma1 -0.2561 1.1146 -0.1164 -0.9606 s.e. 0.0878 0.0985 0.0965 0.0914 sigma^2 estimated as 4452080: log likelihood = -1741.88, aic = 3493.75 [[3]][[3]] NULL [[3]][[4]] NULL $aic [1] 3493.755 3493.036 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/13dvk1229272871.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 = 192 Frequency = 1 [1] 205.596839 -100.747106 4584.974901 2651.535532 4131.185035 [6] 2929.491463 1127.698852 1634.191646 -39.014746 777.909443 [11] 669.987618 678.713524 1296.380976 1026.435488 -574.155444 [16] -2268.611346 -27.326631 1198.724396 50.516252 169.428128 [21] -332.700754 1066.929195 1426.300123 246.002895 -1351.900107 [26] -658.317676 -1002.595497 2474.069884 -426.796112 -1185.878627 [31] 455.819790 1714.170606 -867.449981 -813.944839 1285.290710 [36] -780.000367 3015.710965 -4291.890195 126.482021 915.346602 [41] 407.482198 -616.989229 646.575624 461.650541 -339.465970 [46] 817.129350 -380.227590 378.480019 -3144.342112 -4199.918756 [51] 774.145763 -1283.238612 704.291515 -1632.265540 1813.871101 [56] 392.349884 -849.003646 -216.300852 1307.333983 -1778.273430 [61] 699.511967 -943.875360 48.210157 -2168.667488 1349.822892 [66] -2026.481679 -364.065864 -426.974213 -1363.393786 425.974536 [71] -1156.092975 -225.138067 -171.309192 -1881.133363 -1193.254286 [76] 4389.391111 -354.968810 -1016.061280 578.051180 -832.558125 [81] 1115.344753 994.725830 1914.499078 -2369.223321 -1127.561890 [86] -1017.061428 1863.696267 -1403.493235 3691.910621 33.602481 [91] -1640.828319 -1252.054066 -656.259717 -19.254883 1683.976565 [96] -24.511391 3033.393788 -4517.623132 194.675044 -321.071337 [101] 884.525015 -249.810916 566.381670 -565.719048 -68.181212 [106] 1758.413296 911.238241 -512.831554 -511.511711 -1180.931148 [111] 779.956521 -1415.603689 2465.213337 -1975.808426 -861.661210 [116] -1355.528511 -2169.993918 -770.090995 1405.679143 569.077423 [121] 962.308496 2157.917373 1697.239191 1465.935166 -3953.418577 [126] -3294.433788 1002.525100 -939.865808 6351.474237 -67.096859 [131] -2516.744003 -2511.579231 -333.228624 -1642.120125 3166.401692 [136] 756.566819 -270.054982 -3181.515629 2465.976974 -932.996709 [141] 835.528906 -1569.531042 -86.703106 -2994.355407 -4310.073085 [146] 2785.651373 1427.298640 -826.963127 1680.914826 -2406.980357 [151] -2278.811615 1792.227259 2623.245197 22.529618 -3327.865976 [156] 1135.307230 126.186989 363.429152 1987.558656 -3.743946 [161] 583.424132 -528.058971 -4118.505147 -1966.630767 -937.354988 [166] 2273.065289 174.206088 -1181.331036 980.456856 -513.893424 [171] -360.285871 1407.022282 3960.599616 -1131.802746 1560.535572 [176] 2639.711132 -1566.539868 599.730573 7460.831724 -3595.560231 [181] 2914.220891 331.382655 -473.236179 1375.359774 -2990.980267 [186] -74.682455 844.984885 -1062.060061 -1106.613875 -215.646233 [191] 3153.983194 13356.591580 > postscript(file="/var/www/html/rcomp/tmp/2arr71229272871.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/33hm31229272871.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/4yk3a1229272871.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/5bu981229272871.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/6lo9o1229272871.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/7vm6k1229272871.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/8ki751229272871.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/9v0hz1229272871.tab") > > system("convert tmp/13dvk1229272871.ps tmp/13dvk1229272871.png") > system("convert tmp/2arr71229272871.ps tmp/2arr71229272871.png") > system("convert tmp/33hm31229272871.ps tmp/33hm31229272871.png") > system("convert tmp/4yk3a1229272871.ps tmp/4yk3a1229272871.png") > system("convert tmp/5bu981229272871.ps tmp/5bu981229272871.png") > system("convert tmp/6lo9o1229272871.ps tmp/6lo9o1229272871.png") > system("convert tmp/7vm6k1229272871.ps tmp/7vm6k1229272871.png") > > > proc.time() user system elapsed 3.274 1.083 3.744