R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) 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(235.1 + ,280.7 + ,264.6 + ,240.7 + ,201.4 + ,240.8 + ,241.1 + ,223.8 + ,206.1 + ,174.7 + ,203.3 + ,220.5 + ,299.5 + ,347.4 + ,338.3 + ,327.7 + ,351.6 + ,396.6 + ,438.8 + ,395.6 + ,363.5 + ,378.8 + ,357 + ,369 + ,464.8 + ,479.1 + ,431.3 + ,366.5 + ,326.3 + ,355.1 + ,331.6 + ,261.3 + ,249 + ,205.5 + ,235.6 + ,240.9 + ,264.9 + ,253.8 + ,232.3 + ,193.8 + ,177 + ,213.2 + ,207.2 + ,180.6 + ,188.6 + ,175.4 + ,199 + ,179.6 + ,225.8 + ,234 + ,200.2 + ,183.6 + ,178.2 + ,203.2 + ,208.5 + ,191.8 + ,172.8 + ,148 + ,159.4 + ,154.5 + ,213.2 + ,196.4 + ,182.8 + ,176.4 + ,153.6 + ,173.2 + ,171 + ,151.2 + ,161.9 + ,157.2 + ,201.7 + ,236.4 + ,356.1 + ,398.3 + ,403.7 + ,384.6 + ,365.8 + ,368.1 + ,367.9 + ,347 + ,343.3 + ,292.9 + ,311.5 + ,300.9 + ,366.9 + ,356.9 + ,329.7 + ,316.2 + ,269 + ,289.3 + ,266.2 + ,253.6 + ,233.8 + ,228.4 + ,253.6 + ,260.1 + ,306.6 + ,309.2 + ,309.5 + ,271 + ,279.9 + ,317.9 + ,298.4 + ,246.7 + ,227.3 + ,209.1 + ,259.9 + ,266 + ,320.6 + ,308.5 + ,282.2 + ,262.7 + ,263.5 + ,313.1 + ,284.3 + ,252.6 + ,250.3 + ,246.5 + ,312.7 + ,333.2 + ,446.4 + ,511.6 + ,515.5 + ,506.4 + ,483.2 + ,522.3 + ,509.8 + ,460.7 + ,405.8 + ,375 + ,378.5 + ,406.8 + ,467.8 + ,469.8 + ,429.8 + ,355.8 + ,332.7 + ,378 + ,360.5 + ,334.7 + ,319.5 + ,323.1 + ,363.6 + ,352.1 + ,411.9 + ,388.6 + ,416.4 + ,360.7 + ,338 + ,417.2 + ,388.4 + ,371.1 + ,331.5 + ,353.7 + ,396.7 + ,447 + ,533.5 + ,565.4 + ,542.3 + ,488.7 + ,467.1 + ,531.3 + ,496.1 + ,444 + ,403.4 + ,386.3 + ,394.1 + ,404.1 + ,462.1 + ,448.1 + ,432.3 + ,386.3 + ,395.2 + ,421.9 + ,382.9 + ,384.2 + ,345.5 + ,323.4 + ,372.6 + ,376 + ,462.7 + ,487 + ,444.2 + ,399.3 + ,394.9 + ,455.4 + ,414 + ,375.5 + ,347 + ,339.4 + ,385.8 + ,378.8 + ,451.8 + ,446.1 + ,422.5 + ,383.1 + ,352.8 + ,445.3 + ,367.5 + ,355.1 + ,326.2 + ,319.8 + ,331.8 + ,340.9 + ,394.1 + ,417.2 + ,369.9 + ,349.2 + ,321.4 + ,405.7 + ,342.9 + ,316.5 + ,284.2 + ,270.9 + ,288.8 + ,278.8 + ,324.4 + ,310.9 + ,299 + ,273 + ,279.3 + ,359.2 + ,305 + ,282.1 + ,250.3 + ,246.5 + ,257.9 + ,266.5 + ,315.9 + ,318.4 + ,295.4 + ,266.4 + ,245.8 + ,362.8 + ,324.9 + ,294.2 + ,289.5 + ,295.2 + ,290.3 + ,272 + ,307.4 + ,328.7 + ,292.9 + ,249.1 + ,230.4 + ,361.5 + ,321.7 + ,277.2 + ,260.7 + ,251 + ,257.6 + ,241.8 + ,287.5 + ,292.3 + ,274.7 + ,254.2 + ,230 + ,339 + ,318.2 + ,287 + ,295.8 + ,284 + ,271 + ,262.7 + ,340.6 + ,379.4 + ,373.3 + ,355.2 + ,338.4 + ,466.9 + ,451 + ,422 + ,429.2 + ,425.9 + ,460.7 + ,463.6 + ,541.4 + ,544.2 + ,517.5 + ,469.4 + ,439.4 + ,549 + ,533 + ,506.1 + ,484 + ,457 + ,481.5 + ,469.5 + ,544.7 + ,541.2 + ,521.5 + ,469.7 + ,434.4 + ,542.6 + ,517.3 + ,485.7 + ,465.8 + ,447 + ,426.6 + ,411.6 + ,467.5 + ,484.5 + ,451.2 + ,417.4 + ,379.9 + ,484.7 + ,455 + ,420.8 + ,416.5 + ,376.3 + ,405.6 + ,405.8 + ,500.8 + ,514 + ,475.5 + ,430.1 + ,414.4 + ,538 + ,526 + ,488.5 + ,520.2 + ,504.4 + ,568.5 + ,610.6 + ,818 + ,830.9 + ,835.9 + ,782 + ,762.3 + ,856.9 + ,820.9 + ,769.6 + ,752.2 + ,724.4 + ,723.1 + ,719.5 + ,817.4 + ,803.3 + ,752.5 + ,689 + ,630.4 + ,765.5 + ,757.7 + ,732.2 + ,702.6 + ,683.3 + ,709.5 + ,702.2 + ,784.8 + ,810.9 + ,755.6 + ,656.8 + ,615.1 + ,745.3 + ,694.1 + ,675.7 + ,643.7 + ,622.1 + ,634.6 + ,588 + ,689.7 + ,673.9 + ,647.9 + ,568.8 + ,545.7 + ,632.6 + ,643.8 + ,593.1 + ,579.7 + ,546 + ,562.9 + ,572.5) > par9 = '1' > par8 = '2' > par7 = '0' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '1' > par2 = '0.5' > par1 = 'FALSE' > 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,] 0.09800037 0.2275817 0.06545319 -0.08906671 -0.05261153 -0.6512133 [2,] 0.09532331 0.2322662 0.06522958 -0.04302645 0.00000000 -0.6971436 [3,] 0.09383457 0.2349777 0.06552424 0.00000000 0.00000000 -0.7206857 [4,] 0.10943366 0.2417305 0.00000000 0.00000000 0.00000000 -0.7240061 [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,] 0.06715 2e-05 0.21708 0.42883 0.56057 0 [2,] 0.07353 1e-05 0.21865 0.58119 NA 0 [3,] 0.07770 1e-05 0.21650 NA NA 0 [4,] 0.03485 0e+00 NA NA NA 0 [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 sar1 sar2 sma1 0.0980 0.2276 0.0655 -0.0891 -0.0526 -0.6512 s.e. 0.0534 0.0527 0.0529 0.1124 0.0903 0.1031 sigma^2 estimated as 0.2831: log likelihood = -287.3, aic = 588.59 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 0.0980 0.2276 0.0655 -0.0891 -0.0526 -0.6512 s.e. 0.0534 0.0527 0.0529 0.1124 0.0903 0.1031 sigma^2 estimated as 0.2831: log likelihood = -287.3, aic = 588.59 [[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 sar1 sar2 sma1 0.0953 0.2323 0.0652 -0.0430 0 -0.6971 s.e. 0.0531 0.0520 0.0529 0.0779 0 0.0606 sigma^2 estimated as 0.2833: log likelihood = -287.46, aic = 586.92 [[3]][[4]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, fixed = last.arma$next.vector, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 0.0938 0.2350 0.0655 0 0 -0.7207 s.e. 0.0530 0.0517 0.0529 0 0 0.0405 sigma^2 estimated as 0.2835: log likelihood = -287.61, aic = 585.22 [[3]][[5]] NULL [[3]][[6]] NULL $aic [1] 588.5900 586.9197 585.2218 584.7512 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 3: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE > postscript(file="/var/www/rcomp/tmp/1x6u21323205705.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 = 372 Frequency = 1 [1] 8.852493e-03 5.059755e-03 2.900304e-03 1.498531e-03 -1.255840e-06 [6] 1.218862e-03 1.052759e-03 3.875797e-04 -2.267307e-04 -1.287177e-03 [11] -1.752650e-04 -8.140182e-03 -4.471374e-02 -6.877836e-02 2.000649e-01 [16] 3.696475e-01 1.523025e+00 -3.823482e-01 4.424811e-01 -5.486882e-01 [21] -3.267342e-01 1.304683e+00 -1.349996e+00 -3.894443e-01 1.828760e-01 [26] -8.276559e-01 -5.712034e-01 -7.277738e-01 -4.086168e-01 -7.041021e-02 [31] -8.129118e-01 -8.788897e-01 6.898870e-01 -7.307007e-01 8.351460e-01 [36] -1.381826e-01 -1.626114e+00 -1.100349e+00 4.567750e-01 3.275274e-02 [41] 1.019982e-01 3.143200e-01 -2.802974e-01 3.004584e-01 8.649272e-01 [46] 1.134387e-01 7.343838e-02 -1.194391e+00 -1.518651e-01 -2.104990e-02 [51] -3.433283e-01 5.741814e-01 4.778141e-01 -3.455265e-01 8.696060e-02 [56] 5.905257e-01 -4.900021e-01 -4.226641e-01 -9.503906e-02 -1.009804e-01 [61] 5.093649e-01 -1.006983e+00 3.288283e-01 8.633930e-01 -4.761220e-01 [66] -4.421319e-01 -5.579303e-02 3.272552e-01 8.662980e-01 4.460753e-01 [71] 8.009996e-01 9.133818e-01 1.211067e+00 4.322773e-01 3.074016e-01 [76] -1.633246e-01 -1.710572e-01 -1.039613e+00 2.640970e-02 5.909719e-01 [81] 9.767068e-02 -9.137304e-01 -3.307259e-01 -3.919579e-01 -3.359503e-01 [86] -4.603767e-01 -2.925446e-02 4.961645e-01 -7.336281e-01 -8.171967e-02 [91] -5.156699e-01 5.789090e-01 -3.533256e-01 6.365231e-01 3.839001e-02 [96] -5.717955e-02 -8.582657e-01 -9.099097e-02 7.555125e-01 -5.186482e-01 [101] 9.944924e-01 4.066649e-01 -6.163933e-01 -9.958580e-01 -2.038239e-01 [106] 2.857805e-01 9.928490e-01 -3.263972e-02 -5.721245e-01 -5.525481e-01 [111] -2.402436e-01 3.224116e-01 6.303119e-01 6.014353e-01 -7.332867e-01 [116] -1.600489e-01 3.959854e-01 5.258875e-01 8.190533e-01 1.754173e-01 [121] 7.223069e-01 1.202397e+00 1.810749e-01 2.768015e-02 -4.486870e-01 [126] -2.526816e-01 1.883006e-01 -1.402166e-01 -1.040081e+00 -1.651837e-01 [131] -9.380986e-01 6.841726e-01 -4.201255e-01 -3.549050e-01 -4.402096e-01 [136] -1.118875e+00 6.864000e-02 6.167221e-01 5.744275e-02 2.677025e-01 [141] 1.309088e-01 5.889470e-01 5.729314e-03 -8.849692e-01 -4.289004e-01 [146] -7.174424e-01 1.427723e+00 -3.615310e-01 -3.212372e-01 1.067226e+00 [151] -3.328995e-01 2.675549e-01 -5.588027e-01 9.422446e-01 1.076799e-01 [156] 8.140303e-01 -6.497016e-02 3.456836e-01 -4.732594e-01 -2.409873e-01 [161] 5.531128e-02 1.779921e-01 -2.841913e-01 -4.253902e-01 -2.078116e-01 [166] -1.756651e-01 -7.055437e-01 -6.504157e-02 -2.342959e-01 -4.180309e-01 [171] 6.353207e-02 1.328426e-01 7.941906e-01 -7.337792e-01 -4.994631e-01 [176] 1.082391e+00 -1.956644e-01 -5.754720e-01 5.553359e-01 -2.719271e-01 [181] 3.195925e-01 4.810509e-01 -8.126202e-01 -5.842925e-02 3.193000e-01 [186] 3.401624e-01 -3.804738e-01 -3.881083e-01 1.685144e-01 1.966188e-01 [191] 2.659699e-01 -5.644679e-01 -7.411039e-02 -2.454625e-01 -6.313891e-04 [196] 2.136919e-01 -5.146244e-01 1.105913e+00 -1.140423e+00 2.958851e-01 [201] 1.927161e-01 8.230724e-02 -7.317406e-01 9.931088e-02 -2.912662e-01 [206] 5.267981e-01 -6.262840e-01 5.088767e-01 -2.802800e-01 6.279300e-01 [211] -5.404219e-01 -1.939129e-01 -3.798466e-02 -7.376209e-02 -2.426379e-01 [216] -4.306197e-01 -2.665787e-01 -4.508483e-01 5.432033e-01 2.924375e-01 [221] 6.299609e-01 3.860234e-01 -4.641314e-01 -1.620913e-01 -1.093117e-01 [226] 2.067791e-01 -3.709418e-01 2.058872e-01 -8.681389e-02 -9.244835e-03 [231] -3.502825e-02 2.952155e-02 -3.254577e-01 1.528769e+00 2.277004e-01 [236] -5.755367e-01 5.943165e-01 3.751580e-01 -9.798071e-01 -7.381989e-01 [241] -2.956080e-01 7.822695e-01 -2.847900e-01 -5.080908e-01 -1.011736e-01 [246] 1.695979e+00 8.682970e-02 -9.354380e-01 8.402024e-02 -6.437891e-02 [251] -1.988810e-01 -3.847241e-01 9.668326e-02 3.947596e-02 2.417460e-01 [256] 3.718258e-01 -3.985808e-01 4.535439e-01 6.160556e-01 -1.822354e-01 [261] 7.051255e-01 -2.856305e-01 -9.407481e-01 -1.496190e-02 1.031181e+00 [266] 8.127146e-01 2.431278e-01 1.275204e-01 -1.187735e-01 2.015603e-01 [271] 5.628281e-01 3.918411e-02 3.604706e-01 7.729678e-03 5.200522e-01 [276] 1.393210e-01 -1.011071e-01 -4.843939e-01 -5.775428e-02 -2.175511e-01 [281] -1.188450e-01 -4.036542e-01 6.017860e-01 3.209113e-01 -3.788163e-01 [286] -5.003099e-01 3.155802e-01 -4.622157e-02 -9.596827e-03 -3.805091e-01 [291] 1.611043e-01 -2.158103e-01 -2.314837e-01 -2.873792e-01 2.647658e-01 [296] 1.474380e-01 -1.722583e-01 -1.413358e-01 -8.452499e-01 -7.116999e-02 [301] -9.977078e-02 3.125846e-01 -1.848883e-01 1.422109e-01 -2.589270e-01 [306] -1.839425e-01 5.081252e-02 -2.802827e-03 2.645223e-01 -6.695267e-01 [311] 5.982616e-01 3.156034e-01 5.420341e-01 -1.235996e-01 -4.557681e-01 [316] -1.808290e-01 4.235489e-01 1.946989e-01 3.180940e-01 -1.673341e-01 [321] 8.826204e-01 7.797701e-02 8.229292e-01 8.207858e-01 1.771566e+00 [326] -5.575965e-01 1.844728e-01 -1.926948e-01 1.023246e-01 -1.127663e+00 [331] -3.616974e-02 1.105583e-01 -2.160382e-01 3.126280e-02 -5.552022e-01 [336] -1.052952e-01 -4.176452e-01 -3.630879e-01 -2.599277e-01 -3.040118e-02 [341] -4.254244e-01 2.785791e-01 5.702002e-01 3.179544e-01 -6.060072e-01 [346] 5.432848e-02 1.336015e-01 -2.136251e-01 -6.777024e-01 4.540324e-01 [351] -2.675278e-01 -8.420825e-01 4.274950e-02 2.745411e-01 -4.258803e-01 [356] 4.147830e-01 -3.229346e-01 9.154828e-03 -1.359621e-01 -9.165932e-01 [361] 1.475177e-01 -2.787255e-01 2.970548e-01 -2.494117e-01 2.811480e-01 [366] -6.331740e-01 8.394729e-01 -3.352883e-01 -5.373250e-02 -2.269948e-01 [371] 3.155982e-04 5.165007e-01 > postscript(file="/var/www/rcomp/tmp/2k5w01323205705.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/rcomp/tmp/37fg41323205705.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/rcomp/tmp/4y4el1323205705.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/rcomp/tmp/5tnm11323205705.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/rcomp/tmp/6ix5p1323205705.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/rcomp/tmp/7df4a1323205705.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/rcomp/tmp/8g9ve1323205705.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/rcomp/tmp/9gqg01323205705.tab") > > try(system("convert tmp/1x6u21323205705.ps tmp/1x6u21323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/2k5w01323205705.ps tmp/2k5w01323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/37fg41323205705.ps tmp/37fg41323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/4y4el1323205705.ps tmp/4y4el1323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/5tnm11323205705.ps tmp/5tnm11323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/6ix5p1323205705.ps tmp/6ix5p1323205705.png",intern=TRUE)) character(0) > try(system("convert tmp/7df4a1323205705.ps tmp/7df4a1323205705.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.810 0.390 8.191