R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(8.3,8.2,8.1,8,8.1,8.1,8,7.8,7.7,7.7,7.7,7.6,7.5,7.3,7.2,7.1,7.2,7.2,7.2,6.9,6.8,6.8,6.8,6.9,7,7.2,7.2,7.2,7,7,7.2,7.4,7.8,8,7.8,7.8,7.9,7.9,8,8,8,8,8.2,8.4,8.6,8.6,8.5,8.5,8.4,8.4,8.4,8.5,8.6,8.6,8.6,8.6,8.6,8.5,8.4,8.4,8.3,8.3,8.3,8.6,8.8,8.8,8.5,8.1,7.9,8,8.4,8.5,8.5,8.4,8.3,8.3,8.2,8.1,8.1,8.2,8.2,8.2,8.1,8.1,8,7.8,7.7,7.7,7.7,7.7,7.7,7.5,7.4,7.3,7.4,7.4,7.3,7.3,7.1,7,6.5,6.3,6.3,6.5,6.6,6.5,6.3,6.3,6.3,6.5,6.7,6.7,6.7,6.8,6.7,6.8,6.8,7,7,7.2,7.4,7.6,7.8,7.9,8.1,8.3,8.5,8.7,8.8,8.9,9,9,9.1,9.1,9.1,9.2,9.4,9.4,9.3,9.4,9.4,9.5,9.5,9.4,9.4,9.4,9.3,9.3,9.3,9.3,9.3,9.2,9.1,9.1,9.1,9.1,9.2,9.2,9.2,9.3,9.4,9.4,9.5,9.6,9.7,9.7,9.8,9.9,9.9,9.9,9.8,9.8,9.7,9.7,9.6,9.6,9.6,9.6,9.6,9.7,9.7,9.7,9.7,9.8,9.8,9.8,9.8,9.9,9.9,9.8,9.7,9.6,9.6,9.5,9.3,9.2,9,8.9,8.7,8.5,8.4,8.2,8.1,7.9,7.8,7.6,7.5,7.4,7.2,7.2,7.1,7,7,6.9,6.8,6.7,6.7,6.6,6.6,6.5,6.5,6.4,6.4,6.4,6.4,6.3,6.4,6.4,6.4,6.4,6.4,6.4,6.4,6.5,6.5,6.6,6.6,6.6,6.7,6.7,6.8) > par9 = '1' > par8 = '2' > par7 = '1' > par6 = '3' > par5 = '12' > par4 = '0' > par3 = '2' > 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,] 0.2545107 -0.006635011 -0.3421462 -0.7889268 0.7716432 -0.1487725 [2,] 0.2538090 0.000000000 -0.3431705 -0.7904071 0.7711800 -0.1497879 [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 [13,] NA NA NA NA NA NA [14,] NA NA NA NA NA NA [,7] [1,] -0.7555557 [2,] -0.7549001 [3,] NA [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,] 0.00073 0.91992 0 0 0.00020 0.03876 0.00021 [2,] 0.00071 NA 0 0 0.00017 0.03533 0.00018 [3,] NA NA NA NA NA NA NA [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 0.2545 -0.0066 -0.3421 -0.7889 0.7716 -0.1488 -0.7556 s.e. 0.0744 0.0659 0.0650 0.0521 0.2041 0.0716 0.2009 sigma^2 estimated as 0.009524: log likelihood = 215.65, aic = -415.3 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 0.2545 -0.0066 -0.3421 -0.7889 0.7716 -0.1488 -0.7556 s.e. 0.0744 0.0659 0.0650 0.0521 0.2041 0.0716 0.2009 sigma^2 estimated as 0.009524: log likelihood = 215.65, aic = -415.3 [[3]][[3]] NULL [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL $aic [1] -415.3004 -417.2903 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/1q8du1293278481.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 = 241 Frequency = 1 [1] 3.711872e-03 -1.135919e-02 -8.651890e-06 -5.655755e-06 1.682295e-01 [6] -3.200999e-02 -9.128692e-02 -7.379976e-02 3.161109e-02 6.279848e-02 [11] -9.267928e-03 -7.085131e-02 3.156905e-03 -9.517131e-02 1.444011e-02 [16] -1.404557e-02 1.459413e-01 5.670178e-03 3.314785e-02 -2.022851e-01 [21] 7.554233e-02 1.051433e-01 -3.833854e-02 1.379263e-01 1.144141e-01 [26] 1.899901e-01 -4.280736e-02 1.821444e-02 -1.352975e-01 6.062330e-02 [31] 1.839307e-01 3.647477e-02 2.969565e-01 5.678113e-02 -3.009442e-01 [36] 1.136477e-01 7.421375e-02 -2.184184e-01 3.809605e-02 -6.640886e-02 [41] -1.897439e-02 -1.439730e-02 1.454798e-01 3.946188e-02 6.102392e-02 [46] -6.785527e-02 -1.114829e-01 3.858303e-02 -1.563811e-01 -2.331312e-02 [51] -3.093129e-02 4.805879e-02 5.288074e-02 -5.566502e-02 2.750206e-02 [56] -1.368984e-02 1.649947e-02 -9.941958e-02 -1.103218e-01 6.605475e-02 [61] -1.007466e-01 1.194059e-02 3.061788e-02 2.797931e-01 8.205010e-02 [66] -9.927004e-02 -1.927909e-01 -2.447751e-01 8.771200e-03 1.254272e-01 [71] 2.384738e-01 -6.029339e-02 1.226370e-02 2.105698e-02 -5.016084e-02 [76] 2.263598e-02 -1.351560e-01 -8.583586e-02 1.016954e-01 9.617776e-02 [81] -2.127441e-02 5.545020e-03 -1.001644e-01 7.554581e-02 -1.074771e-01 [86] -1.855656e-01 2.336182e-02 9.441794e-02 2.083368e-03 6.366793e-03 [91] 4.214818e-02 -1.944996e-01 4.338961e-02 -5.269327e-04 1.324971e-01 [96] -1.137186e-02 -9.892717e-02 1.262835e-01 -1.667025e-01 2.226677e-02 [101] -4.077487e-01 -7.186936e-03 1.709825e-01 1.374598e-01 7.514274e-02 [106] -4.208613e-02 -2.610382e-02 1.853697e-01 -3.900057e-03 1.531600e-01 [111] 1.617034e-01 -3.956618e-02 6.097378e-02 1.317224e-01 -1.711540e-01 [116] 7.770832e-02 -2.318304e-02 1.403416e-01 -6.175550e-02 1.609223e-01 [121] 1.114610e-01 3.863821e-02 7.752631e-02 5.676238e-03 4.908017e-02 [126] 4.932928e-02 4.742961e-02 4.033432e-02 -4.791272e-02 -3.029522e-02 [131] -1.076237e-02 -1.243013e-01 -1.467848e-02 -9.829060e-02 -1.002919e-01 [136] 6.010663e-02 4.240036e-02 -1.484794e-01 -1.427568e-01 1.589263e-01 [141] -9.523075e-02 2.701623e-02 -5.317572e-02 -1.015405e-01 4.748776e-02 [146] -1.034552e-03 -1.351190e-01 4.031878e-02 -1.055538e-02 -9.758418e-03 [151] 1.314102e-02 -7.872485e-02 -4.845215e-02 7.064104e-02 -1.579686e-02 [156] 6.628895e-03 1.318099e-01 -2.275311e-02 8.541235e-03 1.479498e-01 [161] 5.120234e-02 -6.757352e-02 9.358031e-02 9.599896e-02 1.355844e-04 [166] -4.630696e-02 7.233369e-02 2.878167e-02 -9.511863e-02 -2.330643e-02 [171] -1.390532e-01 8.923976e-03 -1.264194e-01 -1.775017e-02 -1.130350e-01 [176] 2.474752e-02 1.807379e-04 -2.934634e-03 8.472191e-03 1.055632e-01 [181] -8.169432e-03 -5.945833e-03 1.925197e-02 1.200680e-01 -4.312165e-02 [186] -3.165394e-02 2.842295e-02 9.948426e-02 -7.282088e-02 -1.175579e-01 [191] -3.333024e-02 -6.751451e-02 2.035988e-02 -1.202849e-01 -1.915565e-01 [196] 4.992982e-02 -1.470462e-01 -2.880042e-02 -1.138396e-01 -7.677854e-02 [201] 5.666663e-02 -1.083519e-01 4.508444e-02 -4.568386e-02 4.205838e-02 [206] -6.104714e-02 3.271042e-02 7.290689e-02 -1.118424e-01 1.702913e-01 [211] -1.015720e-02 1.043432e-02 1.428604e-01 -5.038937e-02 -3.526892e-03 [216] 3.510325e-02 9.136060e-02 -7.231807e-02 4.825792e-02 -8.360066e-04 [221] 4.248051e-02 -4.975194e-02 4.675060e-02 6.345427e-02 8.642293e-03 [226] -8.274377e-02 1.861545e-01 -1.564022e-02 -8.762537e-03 3.488573e-02 [231] -1.076688e-02 3.422762e-02 -3.118491e-02 1.220304e-01 -5.766206e-02 [236] 9.334285e-02 1.295261e-03 -4.773810e-02 1.157781e-01 -6.915858e-02 [241] 8.978103e-02 > postscript(file="/var/www/html/rcomp/tmp/2q8du1293278481.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/3q8du1293278481.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/4jzvx1293278481.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/5jzvx1293278481.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/6jzvx1293278481.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/7jzvx1293278481.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/870sq1293278481.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/9i9rb1293278481.tab") > > try(system("convert tmp/1q8du1293278481.ps tmp/1q8du1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/2q8du1293278481.ps tmp/2q8du1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/3q8du1293278481.ps tmp/3q8du1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/4jzvx1293278481.ps tmp/4jzvx1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/5jzvx1293278481.ps tmp/5jzvx1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/6jzvx1293278481.ps tmp/6jzvx1293278481.png",intern=TRUE)) character(0) > try(system("convert tmp/7jzvx1293278481.ps tmp/7jzvx1293278481.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.256 1.493 16.033