R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows" 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. 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,54 + ,22 + ,39 + ,-11 + ,-17 + ,-13 + ,18 + ,-2 + ,-41 + ,-4 + ,-29 + ,-11 + ,56 + ,32 + ,46 + ,-13 + ,-17 + ,-11 + ,18 + ,-3 + ,-38 + ,-3 + ,-33 + ,-11 + ,54 + ,28 + ,40 + ,-10 + ,-17 + ,-11 + ,20 + ,-3 + ,-40 + ,-1 + ,-41 + ,-16 + ,58 + ,30 + ,50 + ,-9 + ,-21 + ,-11 + ,19 + ,-3 + ,-41 + ,3) + ,dim=c(12 + ,154) + ,dimnames=list(c('X_1t' + ,'X_2t' + ,'X_3t' + ,'X_4t' + ,'X_5t' + ,'X_6t' + ,'X_7t' + ,'X_8t' + ,'X_9t' + ,'X_10t' + ,'X_11t' + ,'X_12t') + ,1:154)) > y <- array(NA,dim=c(12,154),dimnames=list(c('X_1t','X_2t','X_3t','X_4t','X_5t','X_6t','X_7t','X_8t','X_9t','X_10t','X_11t','X_12t'),1:154)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '2' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '2' > #'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) > 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 X_2t X_1t X_3t X_4t X_5t X_6t X_7t X_8t X_9t X_10t X_11t X_12t 1 5 -3 17 10 -1 9 -15 -1 23 6 NA 24 2 5 -2 22 16 -4 8 -14 1 23 6 NA 29 3 9 0 29 21 -6 6 -14 1 23 8 NA 29 4 10 1 26 13 -9 3 -16 -4 19 4 NA 25 5 14 11 29 12 -13 21 -24 0 26 8 NA 16 6 19 14 42 15 -13 22 -19 -2 24 10 NA 18 7 18 14 40 17 -10 9 -15 -5 23 9 NA 13 8 16 16 34 17 -12 19 -15 2 27 12 NA 22 9 8 14 46 21 -9 14 -14 0 24 9 NA 15 10 10 10 43 18 -15 14 -13 0 24 11 NA 20 11 12 15 44 15 -14 23 -11 4 26 11 NA 19 12 13 18 40 15 -18 23 -12 2 24 11 NA 18 13 15 18 41 21 -13 27 -10 3 25 11 NA 13 14 3 12 42 24 -2 25 -21 2 27 11 NA 17 15 2 8 35 29 -1 20 -16 2 25 9 NA 17 16 -2 2 40 33 5 19 -14 1 23 8 NA 13 17 1 -2 43 36 8 19 -11 0 24 6 NA 14 18 1 -1 47 31 6 17 -14 0 24 7 NA 13 19 -1 1 41 38 7 12 -12 1 26 8 NA 17 20 -6 -6 44 44 15 13 -14 0 25 6 NA 17 21 -13 -16 38 44 23 13 -12 0 24 5 NA 15 22 -25 -21 35 42 43 11 -18 -3 24 2 NA 9 23 -26 -38 34 32 60 4 -15 -5 22 3 NA 10 24 -9 -32 31 32 36 8 -13 -6 22 3 NA 9 25 1 -22 25 18 28 1 -12 -2 22 7 NA 14 26 3 -31 35 5 23 5 -12 -1 27 8 NA 18 27 6 -22 36 2 23 4 -16 -3 24 7 NA 18 28 2 -26 41 9 22 3 -12 -1 24 7 NA 12 29 5 -19 41 4 22 4 -11 -1 22 6 NA 16 30 5 -20 38 1 24 2 -18 -6 23 6 NA 12 31 0 -24 39 4 32 8 -17 -2 25 7 NA 19 32 -5 -29 45 1 27 -2 -15 -7 23 5 NA 13 33 -4 -28 46 1 27 1 -17 -7 21 5 NA 12 34 -2 -31 48 2 27 0 -19 -5 21 5 NA 13 35 -1 -30 48 0 29 1 -11 -10 22 4 NA 11 36 -8 -32 48 3 38 7 -14 -9 20 4 NA 10 37 -16 -38 45 6 40 1 -14 -7 22 4 NA 16 38 -19 -43 44 7 45 0 -13 -9 22 1 NA 12 39 -28 -51 45 18 50 -3 -15 -9 20 -1 NA 6 40 -11 -43 45 11 43 0 -15 -10 21 3 NA 8 41 -4 -43 45 2 44 3 -12 -9 20 4 -22 6 42 -9 -42 42 -3 44 1 -10 -8 21 3 -26 8 43 -12 -47 43 3 49 3 -13 -9 21 2 -29 8 44 -10 -45 50 12 42 2 -13 -10 21 1 -37 9 45 -2 -38 46 3 36 6 -10 -8 19 4 -34 13 46 -13 -46 46 2 57 2 -8 -7 21 3 -35 8 47 0 -38 45 9 42 3 -10 -8 21 5 -36 11 48 0 -32 49 11 39 9 -14 -6 22 6 -41 8 49 4 -27 46 9 33 12 -11 -7 19 6 -32 10 50 7 -26 45 9 32 8 -10 -3 24 6 -40 15 51 5 -21 49 7 34 7 -13 -6 22 6 -37 12 52 2 -23 47 8 37 9 -12 -6 22 6 -35 13 53 -2 -24 45 13 38 11 -10 -4 22 5 -20 12 54 6 -17 48 11 28 13 -11 -4 24 6 -17 15 55 -3 -23 51 18 31 9 -12 -7 22 5 -18 13 56 1 -16 48 14 28 9 -12 -5 23 6 -19 13 57 0 -22 49 16 30 13 -15 -6 24 5 -20 16 58 -7 -26 51 19 39 14 -11 -7 21 7 -21 14 59 -6 -25 54 17 38 16 -15 -4 20 4 -25 12 60 -4 -21 52 11 39 20 -17 -6 22 5 -23 15 61 -4 -21 52 11 38 19 -12 -5 23 6 -23 14 62 -2 -18 53 11 37 18 -14 -3 23 6 -17 19 63 2 -12 51 14 32 18 -15 -4 22 5 -25 16 64 -5 -19 55 20 32 19 -15 -6 20 3 -26 16 65 -15 -31 53 15 44 16 -13 -8 21 2 -17 11 66 -16 -38 51 13 43 10 -14 -5 21 3 -23 13 67 -18 -38 52 17 42 11 -14 -7 20 3 -26 12 68 -13 -32 54 18 38 17 -14 -8 20 2 -37 11 69 -23 -43 58 25 37 3 -13 -8 17 0 -38 6 70 -10 -33 57 19 35 14 -13 -6 18 4 -35 9 71 -10 -28 52 15 37 15 -10 -7 19 4 -36 6 72 -6 -25 50 14 33 17 -12 -6 19 5 -29 15 73 -3 -19 53 14 24 20 -9 -2 20 6 -29 17 74 -4 -20 50 16 24 19 -12 -4 21 6 -29 13 75 -7 -21 50 19 31 21 -10 -5 20 5 -27 12 76 -7 -19 51 18 25 17 -10 -2 21 5 -29 13 77 -7 -17 53 19 28 15 -11 -4 19 3 -24 10 78 -3 -16 49 20 24 18 -11 -4 22 5 -29 14 79 0 -10 54 20 25 19 -10 -5 20 5 -21 13 80 -5 -16 57 24 16 16 -13 -7 18 5 -20 10 81 -3 -10 58 18 17 21 -10 -5 16 3 -26 11 82 3 -8 56 15 11 26 -6 -6 17 6 -19 12 83 2 -7 60 25 12 23 -9 -4 18 6 -22 7 84 -7 -15 55 23 39 24 -8 -2 19 4 -22 11 85 -1 -7 54 20 19 23 -12 -3 18 6 -15 9 86 0 -6 52 20 14 19 -10 0 20 5 -16 13 87 -3 -6 55 22 15 25 -11 -4 21 4 -22 12 88 4 2 56 25 7 21 -13 -3 18 5 -21 5 89 2 -4 54 22 12 19 -10 -3 19 5 -11 13 90 3 -4 53 26 12 20 -10 -3 19 4 -10 11 91 0 -8 59 27 14 20 -11 -4 19 3 -6 8 92 -10 -10 62 41 9 17 -11 -5 21 2 -8 8 93 -10 -16 63 29 8 25 -11 -5 19 3 -15 8 94 -9 -14 64 33 4 19 -10 -6 19 2 -16 8 95 -22 -30 75 39 7 13 -13 -10 17 -1 -24 0 96 -16 -33 77 27 3 15 -12 -11 16 0 -27 3 97 -18 -40 79 27 5 15 -13 -13 16 -2 -33 0 98 -14 -38 77 25 0 13 -15 -12 17 1 -29 -1 99 -12 -39 82 19 -2 11 -16 -13 16 -2 -34 -1 100 -17 -46 83 15 6 9 -18 -12 15 -2 -37 -4 101 -23 -50 81 19 11 2 -17 -15 16 -2 -31 1 102 -28 -55 78 23 9 -2 -18 -14 16 -6 -33 -1 103 -31 -66 79 23 17 -4 -20 -16 16 -4 -25 0 104 -21 -63 79 7 21 -2 -22 -16 18 -2 -27 -1 105 -19 -56 73 1 21 1 -17 -12 19 0 -21 6 106 -22 -66 72 7 41 -13 -19 -16 16 -5 -32 0 107 -22 -63 67 4 57 -11 -18 -15 16 -4 -31 -3 108 -25 -69 67 -8 65 -14 -26 -17 16 -5 -32 -3 109 -16 -69 50 -14 68 -4 -19 -15 18 -1 -30 4 110 -22 -72 45 -10 73 -9 -23 -14 16 -2 -34 1 111 -21 -69 39 -11 71 -5 -21 -15 15 -4 -35 0 112 -10 -67 39 -10 71 -4 -27 -14 15 -1 -37 -4 113 -7 -64 37 -8 70 -8 -27 -16 16 1 -32 -2 114 -5 -61 30 -8 69 -1 -21 -11 18 1 -28 3 115 -4 -58 24 -7 65 -2 -22 -14 16 -2 -26 2 116 7 -47 27 -8 57 -1 -24 -12 19 1 -24 5 117 6 -44 19 -4 57 8 -21 -11 19 1 -27 6 118 3 -42 19 3 57 8 -21 -13 18 3 -26 6 119 10 -34 25 -5 55 6 -22 -12 17 3 -27 3 120 0 -38 16 -4 65 7 -25 -12 19 1 -27 4 121 -2 -41 20 5 65 2 -21 -10 22 1 -24 7 122 -1 -38 25 3 64 3 -26 -12 19 0 -28 5 123 2 -37 34 6 60 0 -27 -11 19 2 -23 6 124 8 -22 39 10 43 5 -22 -10 16 2 -23 1 125 -6 -37 40 16 47 -1 -22 -12 18 -1 -29 3 126 -4 -36 38 11 40 3 -20 -12 20 1 -25 6 127 4 -25 42 10 31 4 -21 -11 17 0 -24 0 128 7 -15 46 21 27 8 -16 -12 17 1 -20 3 129 3 -17 48 18 24 10 -17 -9 17 1 -22 4 130 3 -19 51 20 23 14 -19 -6 20 3 -24 7 131 8 -12 55 18 17 15 -20 -7 21 2 -27 6 132 3 -17 52 23 16 9 -20 -7 19 0 -25 6 133 -3 -21 55 28 15 8 -20 -10 18 0 -26 6 134 4 -10 58 31 8 10 -19 -8 20 3 -24 6 135 -5 -19 72 38 5 5 -20 -11 17 -2 -26 2 136 -1 -14 70 27 6 4 -25 -12 15 0 -22 2 137 5 -8 70 21 5 8 -25 -11 17 1 -20 2 138 0 -16 63 31 12 8 -22 -11 18 -1 -26 3 139 -6 -14 66 31 8 10 -19 -9 20 -2 -22 -1 140 -13 -30 65 29 17 8 -20 -9 19 -1 -29 -4 141 -15 -33 55 24 22 10 -18 -12 20 -1 -30 4 142 -8 -37 57 27 24 -8 -17 -10 22 1 -26 5 143 -20 -47 60 36 36 -6 -17 -10 20 -2 -30 3 144 -10 -48 63 35 31 -10 -21 -13 21 -5 -33 -1 145 -22 -50 65 44 34 -15 -17 -13 19 -5 -33 -4 146 -25 -56 61 39 47 -21 -22 -12 22 -6 -31 0 147 -10 -47 65 26 33 -24 -24 -14 19 -4 -36 -1 148 -8 -37 63 27 35 -15 -18 -9 21 -3 -43 -1 149 -9 -35 59 17 31 -12 -20 -12 19 -3 -40 3 150 -5 -29 56 20 35 -11 -21 -10 21 -1 -38 2 151 -7 -28 54 22 39 -11 -17 -13 18 -2 -41 -4 152 -11 -29 56 32 46 -13 -17 -11 18 -3 -38 -3 153 -11 -33 54 28 40 -10 -17 -11 20 -3 -40 -1 154 -16 -41 58 30 50 -9 -21 -11 19 -3 -41 3 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X_1t X_3t X_4t X_5t X_6t 26.73879 0.45299 -0.35935 -0.28558 -0.23458 -0.30160 X_7t X_8t X_9t X_10t X_11t X_12t -0.36217 -0.28712 0.17347 1.07798 -0.07576 -0.17400 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -5.928 -2.214 -0.288 2.283 9.630 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 26.73879 6.39738 4.180 6.18e-05 *** X_1t 0.45299 0.04648 9.747 2.96e-16 *** X_3t -0.35935 0.04535 -7.924 2.98e-12 *** X_4t -0.28558 0.04764 -5.994 3.11e-08 *** X_5t -0.23458 0.04284 -5.476 3.14e-07 *** X_6t -0.30160 0.06142 -4.911 3.46e-06 *** X_7t -0.36217 0.10314 -3.511 0.000665 *** X_8t -0.28712 0.21991 -1.306 0.194604 X_9t 0.17347 0.21782 0.796 0.427637 X_10t 1.07798 0.24709 4.363 3.08e-05 *** X_11t -0.07576 0.04791 -1.581 0.116904 X_12t -0.17400 0.12212 -1.425 0.157268 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.941 on 102 degrees of freedom (40 observations deleted due to missingness) Multiple R-squared: 0.906, Adjusted R-squared: 0.8959 F-statistic: 89.4 on 11 and 102 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 + } Error in if (gqarr[mypoint - kp3 + 1, 2] < 0.01) numsignificant1 <- numsignificant1 + : missing value where TRUE/FALSE needed Execution halted