R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-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 <- array(list(1 + ,-19 + ,-3 + ,53 + ,14 + ,24 + ,20 + ,-9 + ,-2 + ,20 + ,6 + ,-29 + ,17 + ,2 + ,-20 + ,-4 + ,50 + ,16 + ,24 + ,19 + ,-12 + ,-4 + ,21 + ,6 + ,-29 + ,13 + ,3 + ,-21 + ,-7 + ,50 + ,19 + ,31 + ,21 + ,-10 + ,-5 + ,20 + ,5 + ,-27 + ,12 + ,4 + ,-19 + ,-7 + ,51 + ,18 + ,25 + ,17 + ,-10 + ,-2 + ,21 + ,5 + ,-29 + ,13 + ,5 + ,-17 + ,-7 + ,53 + ,19 + ,28 + ,15 + ,-11 + ,-4 + ,19 + ,3 + ,-24 + ,10 + ,6 + ,-16 + ,-3 + ,49 + ,20 + ,24 + ,18 + ,-11 + ,-4 + ,22 + ,5 + ,-29 + ,14 + ,7 + ,-10 + ,0 + ,54 + ,20 + ,25 + ,19 + ,-10 + ,-5 + ,20 + ,5 + ,-21 + ,13 + ,8 + ,-16 + ,-5 + ,57 + ,24 + ,16 + ,16 + ,-13 + ,-7 + ,18 + ,5 + ,-20 + ,10 + ,9 + ,-10 + ,-3 + ,58 + ,18 + ,17 + ,21 + ,-10 + ,-5 + ,16 + ,3 + ,-26 + ,11 + ,10 + ,-8 + ,3 + ,56 + ,15 + ,11 + ,26 + ,-6 + ,-6 + ,17 + ,6 + ,-19 + ,12 + ,11 + ,-7 + ,2 + ,60 + ,25 + ,12 + ,23 + ,-9 + ,-4 + ,18 + ,6 + ,-22 + ,7 + ,12 + ,-15 + ,-7 + ,55 + ,23 + ,39 + ,24 + ,-8 + ,-2 + ,19 + ,4 + ,-22 + ,11 + ,13 + ,-7 + ,-1 + 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+ ,-20 + ,-11 + ,17 + ,-2 + ,-26 + ,2 + ,64 + ,-14 + ,-1 + ,70 + ,27 + ,6 + ,4 + ,-25 + ,-12 + ,15 + ,0 + ,-22 + ,2 + ,65 + ,-8 + ,5 + ,70 + ,21 + ,5 + ,8 + ,-25 + ,-11 + ,17 + ,1 + ,-20 + ,2 + ,66 + ,-16 + ,0 + ,63 + ,31 + ,12 + ,8 + ,-22 + ,-11 + ,18 + ,-1 + ,-26 + ,3 + ,67 + ,-14 + ,-6 + ,66 + ,31 + ,8 + ,10 + ,-19 + ,-9 + ,20 + ,-2 + ,-22 + ,-1 + ,68 + ,-30 + ,-13 + ,65 + ,29 + ,17 + ,8 + ,-20 + ,-9 + ,19 + ,-1 + ,-29 + ,-4 + ,69 + ,-33 + ,-15 + ,55 + ,24 + ,22 + ,10 + ,-18 + ,-12 + ,20 + ,-1 + ,-30 + ,4 + ,70 + ,-37 + ,-8 + ,57 + ,27 + ,24 + ,-8 + ,-17 + ,-10 + ,22 + ,1 + ,-26 + ,5 + ,71 + ,-47 + ,-20 + ,60 + ,36 + ,36 + ,-6 + ,-17 + ,-10 + ,20 + ,-2 + ,-30 + ,3 + ,72 + ,-48 + ,-10 + ,63 + ,35 + ,31 + ,-10 + ,-21 + ,-13 + ,21 + ,-5 + ,-33 + ,-1 + ,73 + ,-50 + ,-22 + ,65 + ,44 + ,34 + ,-15 + ,-17 + ,-13 + ,19 + ,-5 + ,-33 + ,-4 + ,74 + ,-56 + ,-25 + ,61 + ,39 + ,47 + ,-21 + ,-22 + ,-12 + ,22 + ,-6 + ,-31 + ,0 + ,75 + ,-47 + ,-10 + ,65 + ,26 + ,33 + ,-24 + ,-24 + ,-14 + ,19 + ,-4 + ,-36 + ,-1 + ,76 + ,-37 + ,-8 + ,63 + ,27 + ,35 + ,-15 + ,-18 + ,-9 + ,21 + ,-3 + ,-43 + ,-1 + ,77 + ,-35 + ,-9 + ,59 + ,17 + ,31 + ,-12 + ,-20 + ,-12 + ,19 + ,-3 + ,-40 + ,3 + ,78 + ,-29 + ,-5 + ,56 + ,20 + ,35 + ,-11 + ,-21 + ,-10 + ,21 + ,-1 + ,-38 + ,2 + ,79 + ,-28 + ,-7 + ,54 + ,22 + ,39 + ,-11 + ,-17 + ,-13 + ,18 + ,-2 + ,-41 + ,-4 + ,80 + ,-29 + ,-11 + ,56 + ,32 + ,46 + ,-13 + ,-17 + ,-11 + ,18 + ,-3 + ,-38 + ,-3 + ,81 + ,-33 + ,-11 + ,54 + ,28 + ,40 + ,-10 + ,-17 + ,-11 + ,20 + ,-3 + ,-40 + ,-1 + ,82 + ,-41 + ,-16 + ,58 + ,30 + ,50 + ,-9 + ,-21 + ,-11 + ,19 + ,-3 + ,-41 + ,3) + ,dim=c(13 + ,82) + ,dimnames=list(c('maand' + ,'X_1t' + ,'Yt' + ,'X_2t' + ,'X_3t' + ,'X_4t' + ,'X_5t' + ,'X_6t' + ,'X_7t' + ,'X_8t' + ,'X_9t' + ,'X_10t' + ,'X_11t') + ,1:82)) > y <- array(NA,dim=c(13,82),dimnames=list(c('maand','X_1t','Yt','X_2t','X_3t','X_4t','X_5t','X_6t','X_7t','X_8t','X_9t','X_10t','X_11t'),1:82)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '3' > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Yt maand X_1t X_2t X_3t X_4t X_5t X_6t X_7t X_8t X_9t X_10t X_11t t 1 -3 1 -19 53 14 24 20 -9 -2 20 6 -29 17 1 2 -4 2 -20 50 16 24 19 -12 -4 21 6 -29 13 2 3 -7 3 -21 50 19 31 21 -10 -5 20 5 -27 12 3 4 -7 4 -19 51 18 25 17 -10 -2 21 5 -29 13 4 5 -7 5 -17 53 19 28 15 -11 -4 19 3 -24 10 5 6 -3 6 -16 49 20 24 18 -11 -4 22 5 -29 14 6 7 0 7 -10 54 20 25 19 -10 -5 20 5 -21 13 7 8 -5 8 -16 57 24 16 16 -13 -7 18 5 -20 10 8 9 -3 9 -10 58 18 17 21 -10 -5 16 3 -26 11 9 10 3 10 -8 56 15 11 26 -6 -6 17 6 -19 12 10 11 2 11 -7 60 25 12 23 -9 -4 18 6 -22 7 11 12 -7 12 -15 55 23 39 24 -8 -2 19 4 -22 11 12 13 -1 13 -7 54 20 19 23 -12 -3 18 6 -15 9 13 14 0 14 -6 52 20 14 19 -10 0 20 5 -16 13 14 15 -3 15 -6 55 22 15 25 -11 -4 21 4 -22 12 15 16 4 16 2 56 25 7 21 -13 -3 18 5 -21 5 16 17 2 17 -4 54 22 12 19 -10 -3 19 5 -11 13 17 18 3 18 -4 53 26 12 20 -10 -3 19 4 -10 11 18 19 0 19 -8 59 27 14 20 -11 -4 19 3 -6 8 19 20 -10 20 -10 62 41 9 17 -11 -5 21 2 -8 8 20 21 -10 21 -16 63 29 8 25 -11 -5 19 3 -15 8 21 22 -9 22 -14 64 33 4 19 -10 -6 19 2 -16 8 22 23 -22 23 -30 75 39 7 13 -13 -10 17 -1 -24 0 23 24 -16 24 -33 77 27 3 15 -12 -11 16 0 -27 3 24 25 -18 25 -40 79 27 5 15 -13 -13 16 -2 -33 0 25 26 -14 26 -38 77 25 0 13 -15 -12 17 1 -29 -1 26 27 -12 27 -39 82 19 -2 11 -16 -13 16 -2 -34 -1 27 28 -17 28 -46 83 15 6 9 -18 -12 15 -2 -37 -4 28 29 -23 29 -50 81 19 11 2 -17 -15 16 -2 -31 1 29 30 -28 30 -55 78 23 9 -2 -18 -14 16 -6 -33 -1 30 31 -31 31 -66 79 23 17 -4 -20 -16 16 -4 -25 0 31 32 -21 32 -63 79 7 21 -2 -22 -16 18 -2 -27 -1 32 33 -19 33 -56 73 1 21 1 -17 -12 19 0 -21 6 33 34 -22 34 -66 72 7 41 -13 -19 -16 16 -5 -32 0 34 35 -22 35 -63 67 4 57 -11 -18 -15 16 -4 -31 -3 35 36 -25 36 -69 67 -8 65 -14 -26 -17 16 -5 -32 -3 36 37 -16 37 -69 50 -14 68 -4 -19 -15 18 -1 -30 4 37 38 -22 38 -72 45 -10 73 -9 -23 -14 16 -2 -34 1 38 39 -21 39 -69 39 -11 71 -5 -21 -15 15 -4 -35 0 39 40 -10 40 -67 39 -10 71 -4 -27 -14 15 -1 -37 -4 40 41 -7 41 -64 37 -8 70 -8 -27 -16 16 1 -32 -2 41 42 -5 42 -61 30 -8 69 -1 -21 -11 18 1 -28 3 42 43 -4 43 -58 24 -7 65 -2 -22 -14 16 -2 -26 2 43 44 7 44 -47 27 -8 57 -1 -24 -12 19 1 -24 5 44 45 6 45 -44 19 -4 57 8 -21 -11 19 1 -27 6 45 46 3 46 -42 19 3 57 8 -21 -13 18 3 -26 6 46 47 10 47 -34 25 -5 55 6 -22 -12 17 3 -27 3 47 48 0 48 -38 16 -4 65 7 -25 -12 19 1 -27 4 48 49 -2 49 -41 20 5 65 2 -21 -10 22 1 -24 7 49 50 -1 50 -38 25 3 64 3 -26 -12 19 0 -28 5 50 51 2 51 -37 34 6 60 0 -27 -11 19 2 -23 6 51 52 8 52 -22 39 10 43 5 -22 -10 16 2 -23 1 52 53 -6 53 -37 40 16 47 -1 -22 -12 18 -1 -29 3 53 54 -4 54 -36 38 11 40 3 -20 -12 20 1 -25 6 54 55 4 55 -25 42 10 31 4 -21 -11 17 0 -24 0 55 56 7 56 -15 46 21 27 8 -16 -12 17 1 -20 3 56 57 3 57 -17 48 18 24 10 -17 -9 17 1 -22 4 57 58 3 58 -19 51 20 23 14 -19 -6 20 3 -24 7 58 59 8 59 -12 55 18 17 15 -20 -7 21 2 -27 6 59 60 3 60 -17 52 23 16 9 -20 -7 19 0 -25 6 60 61 -3 61 -21 55 28 15 8 -20 -10 18 0 -26 6 61 62 4 62 -10 58 31 8 10 -19 -8 20 3 -24 6 62 63 -5 63 -19 72 38 5 5 -20 -11 17 -2 -26 2 63 64 -1 64 -14 70 27 6 4 -25 -12 15 0 -22 2 64 65 5 65 -8 70 21 5 8 -25 -11 17 1 -20 2 65 66 0 66 -16 63 31 12 8 -22 -11 18 -1 -26 3 66 67 -6 67 -14 66 31 8 10 -19 -9 20 -2 -22 -1 67 68 -13 68 -30 65 29 17 8 -20 -9 19 -1 -29 -4 68 69 -15 69 -33 55 24 22 10 -18 -12 20 -1 -30 4 69 70 -8 70 -37 57 27 24 -8 -17 -10 22 1 -26 5 70 71 -20 71 -47 60 36 36 -6 -17 -10 20 -2 -30 3 71 72 -10 72 -48 63 35 31 -10 -21 -13 21 -5 -33 -1 72 73 -22 73 -50 65 44 34 -15 -17 -13 19 -5 -33 -4 73 74 -25 74 -56 61 39 47 -21 -22 -12 22 -6 -31 0 74 75 -10 75 -47 65 26 33 -24 -24 -14 19 -4 -36 -1 75 76 -8 76 -37 63 27 35 -15 -18 -9 21 -3 -43 -1 76 77 -9 77 -35 59 17 31 -12 -20 -12 19 -3 -40 3 77 78 -5 78 -29 56 20 35 -11 -21 -10 21 -1 -38 2 78 79 -7 79 -28 54 22 39 -11 -17 -13 18 -2 -41 -4 79 80 -11 80 -29 56 32 46 -13 -17 -11 18 -3 -38 -3 80 81 -11 81 -33 54 28 40 -10 -17 -11 20 -3 -40 -1 81 82 -16 82 -41 58 30 50 -9 -21 -11 19 -3 -41 3 82 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) maand X_1t X_2t X_3t X_4t 31.25234 0.06926 0.39249 -0.33041 -0.28196 -0.19717 X_5t X_6t X_7t X_8t X_9t X_10t -0.21757 -0.23029 -0.10110 -0.14327 1.01434 0.02255 X_11t t -0.16966 NA > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -6.7496 -2.1080 -0.0473 1.9025 9.7261 Coefficients: (1 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 31.25234 9.11300 3.429 0.001025 ** maand 0.06926 0.04060 1.706 0.092496 . X_1t 0.39249 0.06098 6.436 1.38e-08 *** X_2t -0.33041 0.06118 -5.401 8.88e-07 *** X_3t -0.28196 0.05984 -4.712 1.23e-05 *** X_4t -0.19717 0.05614 -3.512 0.000788 *** X_5t -0.21757 0.08544 -2.547 0.013115 * X_6t -0.23029 0.14596 -1.578 0.119196 X_7t -0.10110 0.27384 -0.369 0.713111 X_8t -0.14327 0.31403 -0.456 0.649651 X_9t 1.01434 0.31690 3.201 0.002072 ** X_10t 0.02255 0.06655 0.339 0.735727 X_11t -0.16966 0.16236 -1.045 0.299708 t NA NA NA NA --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.984 on 69 degrees of freedom Multiple R-squared: 0.9195, Adjusted R-squared: 0.9055 F-statistic: 65.65 on 12 and 69 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.07560596 0.15121193 0.9243940 [2,] 0.05999438 0.11998876 0.9400056 [3,] 0.09980774 0.19961549 0.9001923 [4,] 0.22419245 0.44838491 0.7758075 [5,] 0.14063353 0.28126706 0.8593665 [6,] 0.08628745 0.17257489 0.9137126 [7,] 0.06055239 0.12110479 0.9394476 [8,] 0.04556192 0.09112384 0.9544381 [9,] 0.06034619 0.12069238 0.9396538 [10,] 0.03512375 0.07024750 0.9648762 [11,] 0.02847161 0.05694322 0.9715284 [12,] 0.01951087 0.03902174 0.9804891 [13,] 0.02956310 0.05912619 0.9704369 [14,] 0.02116423 0.04232845 0.9788358 [15,] 0.01997048 0.03994097 0.9800295 [16,] 0.01249783 0.02499567 0.9875022 [17,] 0.02367217 0.04734434 0.9763278 [18,] 0.02599443 0.05198886 0.9740056 [19,] 0.01848546 0.03697093 0.9815145 [20,] 0.01641197 0.03282394 0.9835880 [21,] 0.01464599 0.02929199 0.9853540 [22,] 0.01320464 0.02640927 0.9867954 [23,] 0.02332350 0.04664700 0.9766765 [24,] 0.09533740 0.19067480 0.9046626 [25,] 0.10634856 0.21269713 0.8936514 [26,] 0.13466717 0.26933433 0.8653328 [27,] 0.12914547 0.25829094 0.8708545 [28,] 0.17419371 0.34838742 0.8258063 [29,] 0.21397305 0.42794609 0.7860270 [30,] 0.21387487 0.42774975 0.7861251 [31,] 0.24013387 0.48026774 0.7598661 [32,] 0.30753343 0.61506685 0.6924666 [33,] 0.25616414 0.51232828 0.7438359 [34,] 0.21006374 0.42012747 0.7899363 [35,] 0.18542381 0.37084761 0.8145762 [36,] 0.16162738 0.32325476 0.8383726 [37,] 0.20143597 0.40287194 0.7985640 [38,] 0.38132227 0.76264453 0.6186777 [39,] 0.32267346 0.64534693 0.6773265 [40,] 0.26108664 0.52217327 0.7389134 [41,] 0.21112575 0.42225150 0.7888742 [42,] 0.16798233 0.33596466 0.8320177 [43,] 0.13999454 0.27998908 0.8600055 [44,] 0.20184611 0.40369222 0.7981539 [45,] 0.20560942 0.41121884 0.7943906 [46,] 0.13528322 0.27056645 0.8647168 [47,] 0.12704596 0.25409193 0.8729540 [48,] 0.08429286 0.16858572 0.9157071 [49,] 0.04175775 0.08351549 0.9582423 > postscript(file="/var/fisher/rcomp/tmp/1wdoj1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/29q3z1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3jb1k1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4y6cd1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5sb3d1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 82 Frequency = 1 1 2 3 4 5 6 1.72119241 -1.02886910 -0.02865918 -2.22639560 -1.29355356 0.26154457 7 8 9 10 11 12 2.39669715 -2.33688229 0.10271535 1.57864515 2.67662883 3.35551240 13 14 15 16 17 18 -2.88230502 -2.09505008 -1.61800652 -2.11229107 -0.81674887 1.78147035 19 20 21 22 23 24 3.02472068 -1.71450102 -2.08162766 -1.40560176 -3.09820715 0.48192205 25 26 27 28 29 30 3.43779758 0.41873269 4.55390721 1.63280525 -2.15336044 -2.75417504 31 32 33 34 35 36 -2.73563043 0.40277552 -2.71277250 3.40875457 2.03943025 -2.14137349 37 38 39 40 41 42 1.43361038 -4.59537667 -4.53284112 1.15527796 -0.11685399 2.58115630 43 44 45 46 47 48 1.63580647 5.19091576 4.41609738 0.13887498 2.06811337 -5.13964120 49 50 51 52 53 54 -1.26547659 -1.42188841 1.39360222 1.92726992 -1.14716556 -3.05228828 55 56 57 58 59 60 -0.54136918 3.42402611 0.08608319 1.82799281 4.52779847 2.03403918 61 62 63 64 65 66 -0.90297309 0.23333471 3.09144554 -2.38104919 -0.49573932 2.62963337 67 68 69 70 71 72 -2.16180773 -4.24517583 -6.74957860 -1.49422180 -0.80113758 9.72614354 73 74 75 76 77 78 1.26965201 0.10903441 2.57224900 3.86893257 -2.70201448 -2.25031356 79 80 81 82 -3.76821015 -1.70093455 -1.84826484 -0.06600918 > postscript(file="/var/fisher/rcomp/tmp/67hln1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 82 Frequency = 1 lag(myerror, k = 1) myerror 0 1.72119241 NA 1 -1.02886910 1.72119241 2 -0.02865918 -1.02886910 3 -2.22639560 -0.02865918 4 -1.29355356 -2.22639560 5 0.26154457 -1.29355356 6 2.39669715 0.26154457 7 -2.33688229 2.39669715 8 0.10271535 -2.33688229 9 1.57864515 0.10271535 10 2.67662883 1.57864515 11 3.35551240 2.67662883 12 -2.88230502 3.35551240 13 -2.09505008 -2.88230502 14 -1.61800652 -2.09505008 15 -2.11229107 -1.61800652 16 -0.81674887 -2.11229107 17 1.78147035 -0.81674887 18 3.02472068 1.78147035 19 -1.71450102 3.02472068 20 -2.08162766 -1.71450102 21 -1.40560176 -2.08162766 22 -3.09820715 -1.40560176 23 0.48192205 -3.09820715 24 3.43779758 0.48192205 25 0.41873269 3.43779758 26 4.55390721 0.41873269 27 1.63280525 4.55390721 28 -2.15336044 1.63280525 29 -2.75417504 -2.15336044 30 -2.73563043 -2.75417504 31 0.40277552 -2.73563043 32 -2.71277250 0.40277552 33 3.40875457 -2.71277250 34 2.03943025 3.40875457 35 -2.14137349 2.03943025 36 1.43361038 -2.14137349 37 -4.59537667 1.43361038 38 -4.53284112 -4.59537667 39 1.15527796 -4.53284112 40 -0.11685399 1.15527796 41 2.58115630 -0.11685399 42 1.63580647 2.58115630 43 5.19091576 1.63580647 44 4.41609738 5.19091576 45 0.13887498 4.41609738 46 2.06811337 0.13887498 47 -5.13964120 2.06811337 48 -1.26547659 -5.13964120 49 -1.42188841 -1.26547659 50 1.39360222 -1.42188841 51 1.92726992 1.39360222 52 -1.14716556 1.92726992 53 -3.05228828 -1.14716556 54 -0.54136918 -3.05228828 55 3.42402611 -0.54136918 56 0.08608319 3.42402611 57 1.82799281 0.08608319 58 4.52779847 1.82799281 59 2.03403918 4.52779847 60 -0.90297309 2.03403918 61 0.23333471 -0.90297309 62 3.09144554 0.23333471 63 -2.38104919 3.09144554 64 -0.49573932 -2.38104919 65 2.62963337 -0.49573932 66 -2.16180773 2.62963337 67 -4.24517583 -2.16180773 68 -6.74957860 -4.24517583 69 -1.49422180 -6.74957860 70 -0.80113758 -1.49422180 71 9.72614354 -0.80113758 72 1.26965201 9.72614354 73 0.10903441 1.26965201 74 2.57224900 0.10903441 75 3.86893257 2.57224900 76 -2.70201448 3.86893257 77 -2.25031356 -2.70201448 78 -3.76821015 -2.25031356 79 -1.70093455 -3.76821015 80 -1.84826484 -1.70093455 81 -0.06600918 -1.84826484 82 NA -0.06600918 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1.02886910 1.72119241 [2,] -0.02865918 -1.02886910 [3,] -2.22639560 -0.02865918 [4,] -1.29355356 -2.22639560 [5,] 0.26154457 -1.29355356 [6,] 2.39669715 0.26154457 [7,] -2.33688229 2.39669715 [8,] 0.10271535 -2.33688229 [9,] 1.57864515 0.10271535 [10,] 2.67662883 1.57864515 [11,] 3.35551240 2.67662883 [12,] -2.88230502 3.35551240 [13,] -2.09505008 -2.88230502 [14,] -1.61800652 -2.09505008 [15,] -2.11229107 -1.61800652 [16,] -0.81674887 -2.11229107 [17,] 1.78147035 -0.81674887 [18,] 3.02472068 1.78147035 [19,] -1.71450102 3.02472068 [20,] -2.08162766 -1.71450102 [21,] -1.40560176 -2.08162766 [22,] -3.09820715 -1.40560176 [23,] 0.48192205 -3.09820715 [24,] 3.43779758 0.48192205 [25,] 0.41873269 3.43779758 [26,] 4.55390721 0.41873269 [27,] 1.63280525 4.55390721 [28,] -2.15336044 1.63280525 [29,] -2.75417504 -2.15336044 [30,] -2.73563043 -2.75417504 [31,] 0.40277552 -2.73563043 [32,] -2.71277250 0.40277552 [33,] 3.40875457 -2.71277250 [34,] 2.03943025 3.40875457 [35,] -2.14137349 2.03943025 [36,] 1.43361038 -2.14137349 [37,] -4.59537667 1.43361038 [38,] -4.53284112 -4.59537667 [39,] 1.15527796 -4.53284112 [40,] -0.11685399 1.15527796 [41,] 2.58115630 -0.11685399 [42,] 1.63580647 2.58115630 [43,] 5.19091576 1.63580647 [44,] 4.41609738 5.19091576 [45,] 0.13887498 4.41609738 [46,] 2.06811337 0.13887498 [47,] -5.13964120 2.06811337 [48,] -1.26547659 -5.13964120 [49,] -1.42188841 -1.26547659 [50,] 1.39360222 -1.42188841 [51,] 1.92726992 1.39360222 [52,] -1.14716556 1.92726992 [53,] -3.05228828 -1.14716556 [54,] -0.54136918 -3.05228828 [55,] 3.42402611 -0.54136918 [56,] 0.08608319 3.42402611 [57,] 1.82799281 0.08608319 [58,] 4.52779847 1.82799281 [59,] 2.03403918 4.52779847 [60,] -0.90297309 2.03403918 [61,] 0.23333471 -0.90297309 [62,] 3.09144554 0.23333471 [63,] -2.38104919 3.09144554 [64,] -0.49573932 -2.38104919 [65,] 2.62963337 -0.49573932 [66,] -2.16180773 2.62963337 [67,] -4.24517583 -2.16180773 [68,] -6.74957860 -4.24517583 [69,] -1.49422180 -6.74957860 [70,] -0.80113758 -1.49422180 [71,] 9.72614354 -0.80113758 [72,] 1.26965201 9.72614354 [73,] 0.10903441 1.26965201 [74,] 2.57224900 0.10903441 [75,] 3.86893257 2.57224900 [76,] -2.70201448 3.86893257 [77,] -2.25031356 -2.70201448 [78,] -3.76821015 -2.25031356 [79,] -1.70093455 -3.76821015 [80,] -1.84826484 -1.70093455 [81,] -0.06600918 -1.84826484 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1.02886910 1.72119241 2 -0.02865918 -1.02886910 3 -2.22639560 -0.02865918 4 -1.29355356 -2.22639560 5 0.26154457 -1.29355356 6 2.39669715 0.26154457 7 -2.33688229 2.39669715 8 0.10271535 -2.33688229 9 1.57864515 0.10271535 10 2.67662883 1.57864515 11 3.35551240 2.67662883 12 -2.88230502 3.35551240 13 -2.09505008 -2.88230502 14 -1.61800652 -2.09505008 15 -2.11229107 -1.61800652 16 -0.81674887 -2.11229107 17 1.78147035 -0.81674887 18 3.02472068 1.78147035 19 -1.71450102 3.02472068 20 -2.08162766 -1.71450102 21 -1.40560176 -2.08162766 22 -3.09820715 -1.40560176 23 0.48192205 -3.09820715 24 3.43779758 0.48192205 25 0.41873269 3.43779758 26 4.55390721 0.41873269 27 1.63280525 4.55390721 28 -2.15336044 1.63280525 29 -2.75417504 -2.15336044 30 -2.73563043 -2.75417504 31 0.40277552 -2.73563043 32 -2.71277250 0.40277552 33 3.40875457 -2.71277250 34 2.03943025 3.40875457 35 -2.14137349 2.03943025 36 1.43361038 -2.14137349 37 -4.59537667 1.43361038 38 -4.53284112 -4.59537667 39 1.15527796 -4.53284112 40 -0.11685399 1.15527796 41 2.58115630 -0.11685399 42 1.63580647 2.58115630 43 5.19091576 1.63580647 44 4.41609738 5.19091576 45 0.13887498 4.41609738 46 2.06811337 0.13887498 47 -5.13964120 2.06811337 48 -1.26547659 -5.13964120 49 -1.42188841 -1.26547659 50 1.39360222 -1.42188841 51 1.92726992 1.39360222 52 -1.14716556 1.92726992 53 -3.05228828 -1.14716556 54 -0.54136918 -3.05228828 55 3.42402611 -0.54136918 56 0.08608319 3.42402611 57 1.82799281 0.08608319 58 4.52779847 1.82799281 59 2.03403918 4.52779847 60 -0.90297309 2.03403918 61 0.23333471 -0.90297309 62 3.09144554 0.23333471 63 -2.38104919 3.09144554 64 -0.49573932 -2.38104919 65 2.62963337 -0.49573932 66 -2.16180773 2.62963337 67 -4.24517583 -2.16180773 68 -6.74957860 -4.24517583 69 -1.49422180 -6.74957860 70 -0.80113758 -1.49422180 71 9.72614354 -0.80113758 72 1.26965201 9.72614354 73 0.10903441 1.26965201 74 2.57224900 0.10903441 75 3.86893257 2.57224900 76 -2.70201448 3.86893257 77 -2.25031356 -2.70201448 78 -3.76821015 -2.25031356 79 -1.70093455 -3.76821015 80 -1.84826484 -1.70093455 81 -0.06600918 -1.84826484 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/7nyru1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8sx9w1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/9pk2s1352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/10u8u81352143960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } Error: subscript out of bounds Execution halted