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Type 'q()' to quit R. > x <- array(list(0 + ,5 + ,0 + ,100009 + ,100280 + ,111940 + ,97527 + ,90604 + ,0 + ,6 + ,0 + ,95558 + ,100009 + ,100280 + ,111940 + ,97527 + ,0 + ,7 + ,0 + ,98533 + ,95558 + ,100009 + ,100280 + ,111940 + ,0 + ,8 + ,0 + ,92694 + ,98533 + ,95558 + ,100009 + ,100280 + ,0 + ,9 + ,0 + ,97920 + ,92694 + ,98533 + ,95558 + ,100009 + ,0 + ,10 + ,0 + ,110933 + ,97920 + ,92694 + ,98533 + ,95558 + ,0 + ,11 + ,0 + ,110855 + ,110933 + ,97920 + ,92694 + ,98533 + ,0 + ,12 + ,0 + ,111716 + ,110855 + ,110933 + ,97920 + ,92694 + ,0 + ,13 + ,0 + ,96348 + ,111716 + ,110855 + ,110933 + ,97920 + ,0 + ,14 + ,0 + ,105425 + ,96348 + ,111716 + ,110855 + ,110933 + ,0 + ,15 + ,0 + ,114874 + ,105425 + ,96348 + ,111716 + ,110855 + ,0 + ,16 + ,0 + ,104199 + ,114874 + ,105425 + ,96348 + ,111716 + ,0 + ,17 + ,0 + ,101166 + ,104199 + ,114874 + ,105425 + ,96348 + ,0 + ,18 + ,0 + ,99010 + ,101166 + ,104199 + ,114874 + ,105425 + ,0 + ,19 + ,0 + ,101607 + ,99010 + ,101166 + ,104199 + ,114874 + ,0 + 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+ ,104792 + ,102160 + ,109761 + ,99047 + ,1 + ,127 + ,127 + ,112430 + ,104341 + ,104792 + ,102160 + ,109761 + ,1 + ,128 + ,128 + ,113034 + ,112430 + ,104341 + ,104792 + ,102160 + ,1 + ,129 + ,129 + ,114197 + ,113034 + ,112430 + ,104341 + ,104792 + ,1 + ,130 + ,130 + ,127876 + ,114197 + ,113034 + ,112430 + ,104341 + ,1 + ,131 + ,131 + ,135199 + ,127876 + ,114197 + ,113034 + ,112430 + ,1 + ,132 + ,132 + ,123663 + ,135199 + ,127876 + ,114197 + ,113034 + ,1 + ,133 + ,133 + ,112578 + ,123663 + ,135199 + ,127876 + ,114197 + ,1 + ,134 + ,134 + ,117104 + ,112578 + ,123663 + ,135199 + ,127876 + ,1 + ,135 + ,135 + ,139703 + ,117104 + ,112578 + ,123663 + ,135199 + ,1 + ,136 + ,136 + ,114961 + ,139703 + ,117104 + ,112578 + ,123663 + ,1 + ,137 + ,137 + ,134222 + ,114961 + ,139703 + ,117104 + ,112578 + ,1 + ,138 + ,138 + ,128390 + ,134222 + ,114961 + ,139703 + ,117104 + ,1 + ,139 + ,139 + ,134197 + ,128390 + ,134222 + ,114961 + ,139703 + ,1 + ,140 + ,140 + ,135963 + ,134197 + ,128390 + ,134222 + ,114961 + ,1 + ,141 + ,141 + ,135936 + ,135963 + ,134197 + ,128390 + ,134222 + ,1 + ,142 + ,142 + ,146803 + ,135936 + ,135963 + ,134197 + ,128390 + ,1 + ,143 + ,143 + ,143231 + ,146803 + ,135936 + ,135963 + ,134197 + ,1 + ,144 + ,144 + ,131510 + ,143231 + ,146803 + ,135936 + ,135963) + ,dim=c(8 + ,140) + ,dimnames=list(c('crisis_10/8' + ,'t' + ,'t_crisis_10/8' + ,'Totale_goederenvervoer_ton' + ,'Totale_goederenvervoer_ton-1' + ,'Totale_goederenvervoer_ton-2' + ,'Totale_goederenvervoer_ton-3' + ,'Totale_goederenvervoer_ton-4') + ,1:140)) > y <- array(NA,dim=c(8,140),dimnames=list(c('crisis_10/8','t','t_crisis_10/8','Totale_goederenvervoer_ton','Totale_goederenvervoer_ton-1','Totale_goederenvervoer_ton-2','Totale_goederenvervoer_ton-3','Totale_goederenvervoer_ton-4'),1:140)) > 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 = 'Include Monthly Dummies' > par1 = '4' > library(lattice) > library(lmtest) Loading required package: zoo > 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 Totale_goederenvervoer_ton crisis_10/8 t t_crisis_10/8 1 100009 0 5 0 2 95558 0 6 0 3 98533 0 7 0 4 92694 0 8 0 5 97920 0 9 0 6 110933 0 10 0 7 110855 0 11 0 8 111716 0 12 0 9 96348 0 13 0 10 105425 0 14 0 11 114874 0 15 0 12 104199 0 16 0 13 101166 0 17 0 14 99010 0 18 0 15 101607 0 19 0 16 97492 0 20 0 17 106088 0 21 0 18 113536 0 22 0 19 112475 0 23 0 20 115491 0 24 0 21 97733 0 25 0 22 102591 0 26 0 23 114783 0 27 0 24 100397 0 28 0 25 97772 0 29 0 26 96128 0 30 0 27 91261 0 31 0 28 90686 0 32 0 29 97792 0 33 0 30 108848 0 34 0 31 109989 0 35 0 32 109453 0 36 0 33 93945 0 37 0 34 98750 0 38 0 35 119043 0 39 0 36 104776 0 40 0 37 103262 0 41 0 38 106735 0 42 0 39 101600 0 43 0 40 99358 0 44 0 41 105240 0 45 0 42 114079 0 46 0 43 121637 0 47 0 44 111747 0 48 0 45 99496 0 49 0 46 104992 0 50 0 47 124255 0 51 0 48 108258 0 52 0 49 106940 0 53 0 50 104939 0 54 0 51 105896 0 55 0 52 107287 0 56 0 53 110783 0 57 0 54 122139 0 58 0 55 125823 0 59 0 56 120480 0 60 0 57 103296 0 61 0 58 117121 0 62 0 59 129924 0 63 0 60 118589 0 64 0 61 118062 0 65 0 62 113597 0 66 0 63 117161 0 67 0 64 112893 0 68 0 65 119657 0 69 0 66 136562 0 70 0 67 140446 0 71 0 68 138744 0 72 0 69 120324 0 73 0 70 118113 0 74 0 71 130257 0 75 0 72 125510 0 76 0 73 117986 0 77 0 74 118316 0 78 0 75 122075 0 79 0 76 117573 0 80 0 77 122566 0 81 0 78 135934 0 82 0 79 138394 0 83 0 80 137999 0 84 0 81 118780 0 85 0 82 117907 0 86 0 83 142932 0 87 0 84 132200 0 88 0 85 125666 0 89 0 86 127958 0 90 0 87 127718 0 91 0 88 124368 0 92 0 89 135241 0 93 0 90 144734 0 94 0 91 142320 0 95 0 92 141481 0 96 0 93 120471 0 97 0 94 123422 0 98 0 95 145829 0 99 0 96 134572 0 100 0 97 132156 0 101 0 98 140265 0 102 0 99 137771 0 103 0 100 134035 0 104 0 101 144016 0 105 0 102 151905 0 106 0 103 155791 0 107 0 104 148440 0 108 0 105 129862 0 109 0 106 134264 0 110 0 107 151952 0 111 0 108 143191 0 112 0 109 137242 0 113 0 110 136993 0 114 0 111 134431 0 115 0 112 132523 0 116 0 113 133486 0 117 0 114 140120 0 118 0 115 137521 1 119 119 116 112193 1 120 120 117 94256 1 121 121 118 99047 1 122 122 119 109761 1 123 123 120 102160 1 124 124 121 104792 1 125 125 122 104341 1 126 126 123 112430 1 127 127 124 113034 1 128 128 125 114197 1 129 129 126 127876 1 130 130 127 135199 1 131 131 128 123663 1 132 132 129 112578 1 133 133 130 117104 1 134 134 131 139703 1 135 135 132 114961 1 136 136 133 134222 1 137 137 134 128390 1 138 138 135 134197 1 139 139 136 135963 1 140 140 137 135936 1 141 141 138 146803 1 142 142 139 143231 1 143 143 140 131510 1 144 144 Totale_goederenvervoer_ton-1 Totale_goederenvervoer_ton-2 1 100280 111940 2 100009 100280 3 95558 100009 4 98533 95558 5 92694 98533 6 97920 92694 7 110933 97920 8 110855 110933 9 111716 110855 10 96348 111716 11 105425 96348 12 114874 105425 13 104199 114874 14 101166 104199 15 99010 101166 16 101607 99010 17 97492 101607 18 106088 97492 19 113536 106088 20 112475 113536 21 115491 112475 22 97733 115491 23 102591 97733 24 114783 102591 25 100397 114783 26 97772 100397 27 96128 97772 28 91261 96128 29 90686 91261 30 97792 90686 31 108848 97792 32 109989 108848 33 109453 109989 34 93945 109453 35 98750 93945 36 119043 98750 37 104776 119043 38 103262 104776 39 106735 103262 40 101600 106735 41 99358 101600 42 105240 99358 43 114079 105240 44 121637 114079 45 111747 121637 46 99496 111747 47 104992 99496 48 124255 104992 49 108258 124255 50 106940 108258 51 104939 106940 52 105896 104939 53 107287 105896 54 110783 107287 55 122139 110783 56 125823 122139 57 120480 125823 58 103296 120480 59 117121 103296 60 129924 117121 61 118589 129924 62 118062 118589 63 113597 118062 64 117161 113597 65 112893 117161 66 119657 112893 67 136562 119657 68 140446 136562 69 138744 140446 70 120324 138744 71 118113 120324 72 130257 118113 73 125510 130257 74 117986 125510 75 118316 117986 76 122075 118316 77 117573 122075 78 122566 117573 79 135934 122566 80 138394 135934 81 137999 138394 82 118780 137999 83 117907 118780 84 142932 117907 85 132200 142932 86 125666 132200 87 127958 125666 88 127718 127958 89 124368 127718 90 135241 124368 91 144734 135241 92 142320 144734 93 141481 142320 94 120471 141481 95 123422 120471 96 145829 123422 97 134572 145829 98 132156 134572 99 140265 132156 100 137771 140265 101 134035 137771 102 144016 134035 103 151905 144016 104 155791 151905 105 148440 155791 106 129862 148440 107 134264 129862 108 151952 134264 109 143191 151952 110 137242 143191 111 136993 137242 112 134431 136993 113 132523 134431 114 133486 132523 115 140120 133486 116 137521 140120 117 112193 137521 118 94256 112193 119 99047 94256 120 109761 99047 121 102160 109761 122 104792 102160 123 104341 104792 124 112430 104341 125 113034 112430 126 114197 113034 127 127876 114197 128 135199 127876 129 123663 135199 130 112578 123663 131 117104 112578 132 139703 117104 133 114961 139703 134 134222 114961 135 128390 134222 136 134197 128390 137 135963 134197 138 135936 135963 139 146803 135936 140 143231 146803 Totale_goederenvervoer_ton-3 Totale_goederenvervoer_ton-4 M1 M2 M3 M4 M5 M6 1 97527 90604 1 0 0 0 0 0 2 111940 97527 0 1 0 0 0 0 3 100280 111940 0 0 1 0 0 0 4 100009 100280 0 0 0 1 0 0 5 95558 100009 0 0 0 0 1 0 6 98533 95558 0 0 0 0 0 1 7 92694 98533 0 0 0 0 0 0 8 97920 92694 0 0 0 0 0 0 9 110933 97920 0 0 0 0 0 0 10 110855 110933 0 0 0 0 0 0 11 111716 110855 0 0 0 0 0 0 12 96348 111716 0 0 0 0 0 0 13 105425 96348 1 0 0 0 0 0 14 114874 105425 0 1 0 0 0 0 15 104199 114874 0 0 1 0 0 0 16 101166 104199 0 0 0 1 0 0 17 99010 101166 0 0 0 0 1 0 18 101607 99010 0 0 0 0 0 1 19 97492 101607 0 0 0 0 0 0 20 106088 97492 0 0 0 0 0 0 21 113536 106088 0 0 0 0 0 0 22 112475 113536 0 0 0 0 0 0 23 115491 112475 0 0 0 0 0 0 24 97733 115491 0 0 0 0 0 0 25 102591 97733 1 0 0 0 0 0 26 114783 102591 0 1 0 0 0 0 27 100397 114783 0 0 1 0 0 0 28 97772 100397 0 0 0 1 0 0 29 96128 97772 0 0 0 0 1 0 30 91261 96128 0 0 0 0 0 1 31 90686 91261 0 0 0 0 0 0 32 97792 90686 0 0 0 0 0 0 33 108848 97792 0 0 0 0 0 0 34 109989 108848 0 0 0 0 0 0 35 109453 109989 0 0 0 0 0 0 36 93945 109453 0 0 0 0 0 0 37 98750 93945 1 0 0 0 0 0 38 119043 98750 0 1 0 0 0 0 39 104776 119043 0 0 1 0 0 0 40 103262 104776 0 0 0 1 0 0 41 106735 103262 0 0 0 0 1 0 42 101600 106735 0 0 0 0 0 1 43 99358 101600 0 0 0 0 0 0 44 105240 99358 0 0 0 0 0 0 45 114079 105240 0 0 0 0 0 0 46 121637 114079 0 0 0 0 0 0 47 111747 121637 0 0 0 0 0 0 48 99496 111747 0 0 0 0 0 0 49 104992 99496 1 0 0 0 0 0 50 124255 104992 0 1 0 0 0 0 51 108258 124255 0 0 1 0 0 0 52 106940 108258 0 0 0 1 0 0 53 104939 106940 0 0 0 0 1 0 54 105896 104939 0 0 0 0 0 1 55 107287 105896 0 0 0 0 0 0 56 110783 107287 0 0 0 0 0 0 57 122139 110783 0 0 0 0 0 0 58 125823 122139 0 0 0 0 0 0 59 120480 125823 0 0 0 0 0 0 60 103296 120480 0 0 0 0 0 0 61 117121 103296 1 0 0 0 0 0 62 129924 117121 0 1 0 0 0 0 63 118589 129924 0 0 1 0 0 0 64 118062 118589 0 0 0 1 0 0 65 113597 118062 0 0 0 0 1 0 66 117161 113597 0 0 0 0 0 1 67 112893 117161 0 0 0 0 0 0 68 119657 112893 0 0 0 0 0 0 69 136562 119657 0 0 0 0 0 0 70 140446 136562 0 0 0 0 0 0 71 138744 140446 0 0 0 0 0 0 72 120324 138744 0 0 0 0 0 0 73 118113 120324 1 0 0 0 0 0 74 130257 118113 0 1 0 0 0 0 75 125510 130257 0 0 1 0 0 0 76 117986 125510 0 0 0 1 0 0 77 118316 117986 0 0 0 0 1 0 78 122075 118316 0 0 0 0 0 1 79 117573 122075 0 0 0 0 0 0 80 122566 117573 0 0 0 0 0 0 81 135934 122566 0 0 0 0 0 0 82 138394 135934 0 0 0 0 0 0 83 137999 138394 0 0 0 0 0 0 84 118780 137999 0 0 0 0 0 0 85 117907 118780 1 0 0 0 0 0 86 142932 117907 0 1 0 0 0 0 87 132200 142932 0 0 1 0 0 0 88 125666 132200 0 0 0 1 0 0 89 127958 125666 0 0 0 0 1 0 90 127718 127958 0 0 0 0 0 1 91 124368 127718 0 0 0 0 0 0 92 135241 124368 0 0 0 0 0 0 93 144734 135241 0 0 0 0 0 0 94 142320 144734 0 0 0 0 0 0 95 141481 142320 0 0 0 0 0 0 96 120471 141481 0 0 0 0 0 0 97 123422 120471 1 0 0 0 0 0 98 145829 123422 0 1 0 0 0 0 99 134572 145829 0 0 1 0 0 0 100 132156 134572 0 0 0 1 0 0 101 140265 132156 0 0 0 0 1 0 102 137771 140265 0 0 0 0 0 1 103 134035 137771 0 0 0 0 0 0 104 144016 134035 0 0 0 0 0 0 105 151905 144016 0 0 0 0 0 0 106 155791 151905 0 0 0 0 0 0 107 148440 155791 0 0 0 0 0 0 108 129862 148440 0 0 0 0 0 0 109 134264 129862 1 0 0 0 0 0 110 151952 134264 0 1 0 0 0 0 111 143191 151952 0 0 1 0 0 0 112 137242 143191 0 0 0 1 0 0 113 136993 137242 0 0 0 0 1 0 114 134431 136993 0 0 0 0 0 1 115 132523 134431 0 0 0 0 0 0 116 133486 132523 0 0 0 0 0 0 117 140120 133486 0 0 0 0 0 0 118 137521 140120 0 0 0 0 0 0 119 112193 137521 0 0 0 0 0 0 120 94256 112193 0 0 0 0 0 0 121 99047 94256 1 0 0 0 0 0 122 109761 99047 0 1 0 0 0 0 123 102160 109761 0 0 1 0 0 0 124 104792 102160 0 0 0 1 0 0 125 104341 104792 0 0 0 0 1 0 126 112430 104341 0 0 0 0 0 1 127 113034 112430 0 0 0 0 0 0 128 114197 113034 0 0 0 0 0 0 129 127876 114197 0 0 0 0 0 0 130 135199 127876 0 0 0 0 0 0 131 123663 135199 0 0 0 0 0 0 132 112578 123663 0 0 0 0 0 0 133 117104 112578 1 0 0 0 0 0 134 139703 117104 0 1 0 0 0 0 135 114961 139703 0 0 1 0 0 0 136 134222 114961 0 0 0 1 0 0 137 128390 134222 0 0 0 0 1 0 138 134197 128390 0 0 0 0 0 1 139 135963 134197 0 0 0 0 0 0 140 135936 135963 0 0 0 0 0 0 M7 M8 M9 M10 M11 1 0 0 0 0 0 2 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 0 5 0 0 0 0 0 6 0 0 0 0 0 7 1 0 0 0 0 8 0 1 0 0 0 9 0 0 1 0 0 10 0 0 0 1 0 11 0 0 0 0 1 12 0 0 0 0 0 13 0 0 0 0 0 14 0 0 0 0 0 15 0 0 0 0 0 16 0 0 0 0 0 17 0 0 0 0 0 18 0 0 0 0 0 19 1 0 0 0 0 20 0 1 0 0 0 21 0 0 1 0 0 22 0 0 0 1 0 23 0 0 0 0 1 24 0 0 0 0 0 25 0 0 0 0 0 26 0 0 0 0 0 27 0 0 0 0 0 28 0 0 0 0 0 29 0 0 0 0 0 30 0 0 0 0 0 31 1 0 0 0 0 32 0 1 0 0 0 33 0 0 1 0 0 34 0 0 0 1 0 35 0 0 0 0 1 36 0 0 0 0 0 37 0 0 0 0 0 38 0 0 0 0 0 39 0 0 0 0 0 40 0 0 0 0 0 41 0 0 0 0 0 42 0 0 0 0 0 43 1 0 0 0 0 44 0 1 0 0 0 45 0 0 1 0 0 46 0 0 0 1 0 47 0 0 0 0 1 48 0 0 0 0 0 49 0 0 0 0 0 50 0 0 0 0 0 51 0 0 0 0 0 52 0 0 0 0 0 53 0 0 0 0 0 54 0 0 0 0 0 55 1 0 0 0 0 56 0 1 0 0 0 57 0 0 1 0 0 58 0 0 0 1 0 59 0 0 0 0 1 60 0 0 0 0 0 61 0 0 0 0 0 62 0 0 0 0 0 63 0 0 0 0 0 64 0 0 0 0 0 65 0 0 0 0 0 66 0 0 0 0 0 67 1 0 0 0 0 68 0 1 0 0 0 69 0 0 1 0 0 70 0 0 0 1 0 71 0 0 0 0 1 72 0 0 0 0 0 73 0 0 0 0 0 74 0 0 0 0 0 75 0 0 0 0 0 76 0 0 0 0 0 77 0 0 0 0 0 78 0 0 0 0 0 79 1 0 0 0 0 80 0 1 0 0 0 81 0 0 1 0 0 82 0 0 0 1 0 83 0 0 0 0 1 84 0 0 0 0 0 85 0 0 0 0 0 86 0 0 0 0 0 87 0 0 0 0 0 88 0 0 0 0 0 89 0 0 0 0 0 90 0 0 0 0 0 91 1 0 0 0 0 92 0 1 0 0 0 93 0 0 1 0 0 94 0 0 0 1 0 95 0 0 0 0 1 96 0 0 0 0 0 97 0 0 0 0 0 98 0 0 0 0 0 99 0 0 0 0 0 100 0 0 0 0 0 101 0 0 0 0 0 102 0 0 0 0 0 103 1 0 0 0 0 104 0 1 0 0 0 105 0 0 1 0 0 106 0 0 0 1 0 107 0 0 0 0 1 108 0 0 0 0 0 109 0 0 0 0 0 110 0 0 0 0 0 111 0 0 0 0 0 112 0 0 0 0 0 113 0 0 0 0 0 114 0 0 0 0 0 115 1 0 0 0 0 116 0 1 0 0 0 117 0 0 1 0 0 118 0 0 0 1 0 119 0 0 0 0 1 120 0 0 0 0 0 121 0 0 0 0 0 122 0 0 0 0 0 123 0 0 0 0 0 124 0 0 0 0 0 125 0 0 0 0 0 126 0 0 0 0 0 127 1 0 0 0 0 128 0 1 0 0 0 129 0 0 1 0 0 130 0 0 0 1 0 131 0 0 0 0 1 132 0 0 0 0 0 133 0 0 0 0 0 134 0 0 0 0 0 135 0 0 0 0 0 136 0 0 0 0 0 137 0 0 0 0 0 138 0 0 0 0 0 139 1 0 0 0 0 140 0 1 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `crisis_10/8` 3.290e+04 -5.105e+04 t `t_crisis_10/8` 1.505e+02 3.136e+02 `Totale_goederenvervoer_ton-1` `Totale_goederenvervoer_ton-2` 4.894e-01 2.982e-01 `Totale_goederenvervoer_ton-3` `Totale_goederenvervoer_ton-4` 1.534e-01 -3.109e-01 M1 M2 -5.763e+03 -3.547e+03 M3 M4 4.843e+03 -1.585e+03 M5 M6 4.249e+03 1.260e+04 M7 M8 8.948e+03 -2.771e+03 M9 M10 -1.696e+04 3.801e+02 M11 2.115e+04 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -12116.4 -2193.8 -124.1 2126.7 13673.9 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.290e+04 6.735e+03 4.885 3.20e-06 *** `crisis_10/8` -5.105e+04 1.677e+04 -3.045 0.002857 ** t 1.505e+02 2.913e+01 5.169 9.42e-07 *** `t_crisis_10/8` 3.136e+02 1.228e+02 2.554 0.011897 * `Totale_goederenvervoer_ton-1` 4.894e-01 8.883e-02 5.510 2.06e-07 *** `Totale_goederenvervoer_ton-2` 2.982e-01 9.818e-02 3.037 0.002929 ** `Totale_goederenvervoer_ton-3` 1.534e-01 9.660e-02 1.588 0.114923 `Totale_goederenvervoer_ton-4` -3.109e-01 8.304e-02 -3.744 0.000278 *** M1 -5.763e+03 3.451e+03 -1.670 0.097503 . M2 -3.547e+03 3.598e+03 -0.986 0.326174 M3 4.843e+03 2.374e+03 2.040 0.043524 * M4 -1.585e+03 2.545e+03 -0.623 0.534621 M5 4.249e+03 2.707e+03 1.570 0.119123 M6 1.260e+04 2.462e+03 5.116 1.19e-06 *** M7 8.948e+03 2.106e+03 4.249 4.25e-05 *** M8 -2.771e+03 2.827e+03 -0.980 0.329002 M9 -1.696e+04 3.302e+03 -5.137 1.08e-06 *** M10 3.801e+02 3.718e+03 0.102 0.918754 M11 2.115e+04 2.906e+03 7.277 3.73e-11 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3994 on 121 degrees of freedom Multiple R-squared: 0.9451, Adjusted R-squared: 0.937 F-statistic: 115.8 on 18 and 121 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,] 0.4369333946 0.8738667893 0.5630666 [2,] 0.2842347329 0.5684694657 0.7157653 [3,] 0.2424771859 0.4849543718 0.7575228 [4,] 0.1489968178 0.2979936357 0.8510032 [5,] 0.0890949734 0.1781899468 0.9109050 [6,] 0.1177307417 0.2354614835 0.8822693 [7,] 0.0850252722 0.1700505444 0.9149747 [8,] 0.0566613339 0.1133226678 0.9433387 [9,] 0.0510478861 0.1020957722 0.9489521 [10,] 0.0324541545 0.0649083090 0.9675458 [11,] 0.0206581437 0.0413162874 0.9793419 [12,] 0.0113752043 0.0227504086 0.9886248 [13,] 0.0073232544 0.0146465087 0.9926767 [14,] 0.0432057775 0.0864115549 0.9567942 [15,] 0.0342011693 0.0684023386 0.9657988 [16,] 0.0218730832 0.0437461665 0.9781269 [17,] 0.0269871943 0.0539743887 0.9730128 [18,] 0.0181083974 0.0362167949 0.9818916 [19,] 0.0116189844 0.0232379689 0.9883810 [20,] 0.0073460198 0.0146920397 0.9926540 [21,] 0.0044380606 0.0088761212 0.9955619 [22,] 0.0112807637 0.0225615275 0.9887192 [23,] 0.0151924033 0.0303848067 0.9848076 [24,] 0.0101736528 0.0203473055 0.9898263 [25,] 0.0064117208 0.0128234415 0.9935883 [26,] 0.0177728450 0.0355456900 0.9822272 [27,] 0.0135854196 0.0271708392 0.9864146 [28,] 0.0094988769 0.0189977537 0.9905011 [29,] 0.0066269633 0.0132539267 0.9933730 [30,] 0.0051180074 0.0102360148 0.9948820 [31,] 0.0077132909 0.0154265818 0.9922867 [32,] 0.0050505149 0.0101010298 0.9949495 [33,] 0.0033295817 0.0066591633 0.9966704 [34,] 0.0026032427 0.0052064853 0.9973968 [35,] 0.0016963605 0.0033927211 0.9983036 [36,] 0.0014861870 0.0029723739 0.9985138 [37,] 0.0034349944 0.0068699889 0.9965650 [38,] 0.0025893879 0.0051787759 0.9974106 [39,] 0.0019821294 0.0039642588 0.9980179 [40,] 0.0014200668 0.0028401336 0.9985799 [41,] 0.0009996353 0.0019992706 0.9990004 [42,] 0.0007162241 0.0014324482 0.9992838 [43,] 0.0004628652 0.0009257304 0.9995371 [44,] 0.0002727541 0.0005455082 0.9997272 [45,] 0.0005071583 0.0010143166 0.9994928 [46,] 0.0006549291 0.0013098581 0.9993451 [47,] 0.0006895890 0.0013791780 0.9993104 [48,] 0.0005954450 0.0011908899 0.9994046 [49,] 0.0042000365 0.0084000729 0.9958000 [50,] 0.0095875242 0.0191750484 0.9904125 [51,] 0.0179534437 0.0359068874 0.9820466 [52,] 0.0142874894 0.0285749787 0.9857125 [53,] 0.0106563854 0.0213127709 0.9893436 [54,] 0.0088407731 0.0176815461 0.9911592 [55,] 0.0061682539 0.0123365078 0.9938317 [56,] 0.0049481893 0.0098963786 0.9950518 [57,] 0.0032963422 0.0065926844 0.9967037 [58,] 0.0021996636 0.0043993272 0.9978003 [59,] 0.0025460876 0.0050921751 0.9974539 [60,] 0.0017699555 0.0035399110 0.9982300 [61,] 0.0045951127 0.0091902253 0.9954049 [62,] 0.0054669971 0.0109339941 0.9945330 [63,] 0.0066851104 0.0133702209 0.9933149 [64,] 0.0072273583 0.0144547166 0.9927726 [65,] 0.0075596543 0.0151193087 0.9924403 [66,] 0.0059444491 0.0118888983 0.9940556 [67,] 0.0045581362 0.0091162724 0.9954419 [68,] 0.0038593613 0.0077187226 0.9961406 [69,] 0.0025836504 0.0051673009 0.9974163 [70,] 0.0053101062 0.0106202124 0.9946899 [71,] 0.0039701796 0.0079403591 0.9960298 [72,] 0.0034611533 0.0069223066 0.9965388 [73,] 0.0052027148 0.0104054296 0.9947973 [74,] 0.0050077048 0.0100154096 0.9949923 [75,] 0.0040754393 0.0081508786 0.9959246 [76,] 0.0083866751 0.0167733502 0.9916133 [77,] 0.0105435250 0.0210870501 0.9894565 [78,] 0.0080933361 0.0161866722 0.9919067 [79,] 0.0189281606 0.0378563213 0.9810718 [80,] 0.0128486097 0.0256972194 0.9871514 [81,] 0.0083155997 0.0166311994 0.9916844 [82,] 0.0078416977 0.0156833954 0.9921583 [83,] 0.0077322410 0.0154644820 0.9922678 [84,] 0.0048439570 0.0096879140 0.9951560 [85,] 0.0043607550 0.0087215100 0.9956392 [86,] 0.0026655558 0.0053311116 0.9973344 [87,] 0.0509750776 0.1019501552 0.9490249 [88,] 0.0351599275 0.0703198549 0.9648401 [89,] 0.0227481526 0.0454963052 0.9772518 [90,] 0.0150052152 0.0300104305 0.9849948 [91,] 0.0087996248 0.0175992496 0.9912004 [92,] 0.0060799793 0.0121599585 0.9939200 [93,] 0.0040550034 0.0081100067 0.9959450 [94,] 0.0053309171 0.0106618341 0.9946691 [95,] 0.0025036146 0.0050072292 0.9974964 [96,] 0.0048993699 0.0097987397 0.9951006 [97,] 0.0024284073 0.0048568145 0.9975716 > postscript(file="/var/www/rcomp/tmp/1686y1324338323.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/www/rcomp/tmp/2tx441324338323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3squk1324338323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4gd9f1324338323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5maim1324338323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 140 Frequency = 1 1 2 3 4 5 2875.200611 -391.556179 2571.886743 -702.154822 1109.054112 6 7 8 9 10 2966.498750 280.371803 6250.704799 4151.867519 7060.995422 11 12 13 14 15 -4423.193122 1191.183608 7.184547 1524.742408 2115.933647 16 17 18 19 20 796.556696 4035.872178 -1063.559393 -3395.758022 6889.043266 21 22 23 24 25 3540.016675 1177.861932 -5421.996515 -2566.550682 -2440.039446 26 27 28 29 30 -1236.244289 -7059.183320 -2554.488889 -263.988708 -777.515950 31 32 33 34 35 -5093.087174 815.439041 -218.384771 -1891.670347 194.061600 36 37 38 39 40 -2230.147264 -2758.570113 1723.848892 -4702.257417 -3392.503131 41 42 43 44 45 -1869.693130 -1872.014979 1851.823694 -4403.891636 443.679562 46 47 48 49 50 -1017.357816 2159.114483 -5104.984671 -3376.898171 -3575.746472 51 52 53 54 55 -1343.997331 1681.281587 -1875.797349 -1913.016317 -1246.818660 56 57 58 59 60 -314.345711 -2598.123318 6705.336305 -1085.880030 -839.137515 61 62 63 64 65 -1487.094426 -2346.501888 738.682947 -1108.143056 1219.096836 66 67 68 69 70 5652.676431 4507.244241 5067.530147 -129.008437 -5647.575946 71 72 73 74 75 -6376.998375 6883.249698 -1714.081818 -1203.059705 601.044109 76 77 78 79 80 116.763730 -2181.666273 1112.437191 898.706333 4716.449009 81 82 83 84 85 -1502.288222 -6562.791997 4528.909035 5629.733375 -3342.598733 86 87 88 89 90 -1129.494027 343.224771 370.473137 4587.409258 2008.606105 91 92 93 94 95 -4355.835739 2015.009862 -1901.551534 -2586.271443 3102.501131 96 97 98 99 100 3956.183829 -1004.055800 6757.643381 1168.025022 -616.852456 101 102 103 104 105 3957.141413 2480.395912 2825.358597 95.819418 -111.243769 106 107 108 109 110 -58.759858 2433.437583 5262.350904 -2511.913265 -948.225350 111 112 113 114 115 -3311.856704 574.580493 -4560.254844 -6011.567452 4585.574435 116 117 118 119 120 -10934.655220 -2693.507603 3085.279524 -1350.344525 -65.433797 121 122 123 124 125 2079.001376 -227.857450 2939.991139 2916.506202 -4038.040476 126 127 128 129 130 -1301.392626 4587.120959 -3347.472685 1018.543898 -265.045778 131 132 133 134 135 6240.388734 -12116.447484 13673.865239 1052.450680 5938.506392 136 137 138 139 140 1917.980508 -119.133015 -1281.547672 -5444.700466 -6849.630290 > postscript(file="/var/www/rcomp/tmp/6anne1324338323.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 = 140 Frequency = 1 lag(myerror, k = 1) myerror 0 2875.200611 NA 1 -391.556179 2875.200611 2 2571.886743 -391.556179 3 -702.154822 2571.886743 4 1109.054112 -702.154822 5 2966.498750 1109.054112 6 280.371803 2966.498750 7 6250.704799 280.371803 8 4151.867519 6250.704799 9 7060.995422 4151.867519 10 -4423.193122 7060.995422 11 1191.183608 -4423.193122 12 7.184547 1191.183608 13 1524.742408 7.184547 14 2115.933647 1524.742408 15 796.556696 2115.933647 16 4035.872178 796.556696 17 -1063.559393 4035.872178 18 -3395.758022 -1063.559393 19 6889.043266 -3395.758022 20 3540.016675 6889.043266 21 1177.861932 3540.016675 22 -5421.996515 1177.861932 23 -2566.550682 -5421.996515 24 -2440.039446 -2566.550682 25 -1236.244289 -2440.039446 26 -7059.183320 -1236.244289 27 -2554.488889 -7059.183320 28 -263.988708 -2554.488889 29 -777.515950 -263.988708 30 -5093.087174 -777.515950 31 815.439041 -5093.087174 32 -218.384771 815.439041 33 -1891.670347 -218.384771 34 194.061600 -1891.670347 35 -2230.147264 194.061600 36 -2758.570113 -2230.147264 37 1723.848892 -2758.570113 38 -4702.257417 1723.848892 39 -3392.503131 -4702.257417 40 -1869.693130 -3392.503131 41 -1872.014979 -1869.693130 42 1851.823694 -1872.014979 43 -4403.891636 1851.823694 44 443.679562 -4403.891636 45 -1017.357816 443.679562 46 2159.114483 -1017.357816 47 -5104.984671 2159.114483 48 -3376.898171 -5104.984671 49 -3575.746472 -3376.898171 50 -1343.997331 -3575.746472 51 1681.281587 -1343.997331 52 -1875.797349 1681.281587 53 -1913.016317 -1875.797349 54 -1246.818660 -1913.016317 55 -314.345711 -1246.818660 56 -2598.123318 -314.345711 57 6705.336305 -2598.123318 58 -1085.880030 6705.336305 59 -839.137515 -1085.880030 60 -1487.094426 -839.137515 61 -2346.501888 -1487.094426 62 738.682947 -2346.501888 63 -1108.143056 738.682947 64 1219.096836 -1108.143056 65 5652.676431 1219.096836 66 4507.244241 5652.676431 67 5067.530147 4507.244241 68 -129.008437 5067.530147 69 -5647.575946 -129.008437 70 -6376.998375 -5647.575946 71 6883.249698 -6376.998375 72 -1714.081818 6883.249698 73 -1203.059705 -1714.081818 74 601.044109 -1203.059705 75 116.763730 601.044109 76 -2181.666273 116.763730 77 1112.437191 -2181.666273 78 898.706333 1112.437191 79 4716.449009 898.706333 80 -1502.288222 4716.449009 81 -6562.791997 -1502.288222 82 4528.909035 -6562.791997 83 5629.733375 4528.909035 84 -3342.598733 5629.733375 85 -1129.494027 -3342.598733 86 343.224771 -1129.494027 87 370.473137 343.224771 88 4587.409258 370.473137 89 2008.606105 4587.409258 90 -4355.835739 2008.606105 91 2015.009862 -4355.835739 92 -1901.551534 2015.009862 93 -2586.271443 -1901.551534 94 3102.501131 -2586.271443 95 3956.183829 3102.501131 96 -1004.055800 3956.183829 97 6757.643381 -1004.055800 98 1168.025022 6757.643381 99 -616.852456 1168.025022 100 3957.141413 -616.852456 101 2480.395912 3957.141413 102 2825.358597 2480.395912 103 95.819418 2825.358597 104 -111.243769 95.819418 105 -58.759858 -111.243769 106 2433.437583 -58.759858 107 5262.350904 2433.437583 108 -2511.913265 5262.350904 109 -948.225350 -2511.913265 110 -3311.856704 -948.225350 111 574.580493 -3311.856704 112 -4560.254844 574.580493 113 -6011.567452 -4560.254844 114 4585.574435 -6011.567452 115 -10934.655220 4585.574435 116 -2693.507603 -10934.655220 117 3085.279524 -2693.507603 118 -1350.344525 3085.279524 119 -65.433797 -1350.344525 120 2079.001376 -65.433797 121 -227.857450 2079.001376 122 2939.991139 -227.857450 123 2916.506202 2939.991139 124 -4038.040476 2916.506202 125 -1301.392626 -4038.040476 126 4587.120959 -1301.392626 127 -3347.472685 4587.120959 128 1018.543898 -3347.472685 129 -265.045778 1018.543898 130 6240.388734 -265.045778 131 -12116.447484 6240.388734 132 13673.865239 -12116.447484 133 1052.450680 13673.865239 134 5938.506392 1052.450680 135 1917.980508 5938.506392 136 -119.133015 1917.980508 137 -1281.547672 -119.133015 138 -5444.700466 -1281.547672 139 -6849.630290 -5444.700466 140 NA -6849.630290 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -391.556179 2875.200611 [2,] 2571.886743 -391.556179 [3,] -702.154822 2571.886743 [4,] 1109.054112 -702.154822 [5,] 2966.498750 1109.054112 [6,] 280.371803 2966.498750 [7,] 6250.704799 280.371803 [8,] 4151.867519 6250.704799 [9,] 7060.995422 4151.867519 [10,] -4423.193122 7060.995422 [11,] 1191.183608 -4423.193122 [12,] 7.184547 1191.183608 [13,] 1524.742408 7.184547 [14,] 2115.933647 1524.742408 [15,] 796.556696 2115.933647 [16,] 4035.872178 796.556696 [17,] -1063.559393 4035.872178 [18,] -3395.758022 -1063.559393 [19,] 6889.043266 -3395.758022 [20,] 3540.016675 6889.043266 [21,] 1177.861932 3540.016675 [22,] -5421.996515 1177.861932 [23,] -2566.550682 -5421.996515 [24,] -2440.039446 -2566.550682 [25,] -1236.244289 -2440.039446 [26,] -7059.183320 -1236.244289 [27,] -2554.488889 -7059.183320 [28,] -263.988708 -2554.488889 [29,] -777.515950 -263.988708 [30,] -5093.087174 -777.515950 [31,] 815.439041 -5093.087174 [32,] -218.384771 815.439041 [33,] -1891.670347 -218.384771 [34,] 194.061600 -1891.670347 [35,] -2230.147264 194.061600 [36,] -2758.570113 -2230.147264 [37,] 1723.848892 -2758.570113 [38,] -4702.257417 1723.848892 [39,] -3392.503131 -4702.257417 [40,] -1869.693130 -3392.503131 [41,] -1872.014979 -1869.693130 [42,] 1851.823694 -1872.014979 [43,] -4403.891636 1851.823694 [44,] 443.679562 -4403.891636 [45,] -1017.357816 443.679562 [46,] 2159.114483 -1017.357816 [47,] -5104.984671 2159.114483 [48,] -3376.898171 -5104.984671 [49,] -3575.746472 -3376.898171 [50,] -1343.997331 -3575.746472 [51,] 1681.281587 -1343.997331 [52,] -1875.797349 1681.281587 [53,] -1913.016317 -1875.797349 [54,] -1246.818660 -1913.016317 [55,] -314.345711 -1246.818660 [56,] -2598.123318 -314.345711 [57,] 6705.336305 -2598.123318 [58,] -1085.880030 6705.336305 [59,] -839.137515 -1085.880030 [60,] -1487.094426 -839.137515 [61,] -2346.501888 -1487.094426 [62,] 738.682947 -2346.501888 [63,] -1108.143056 738.682947 [64,] 1219.096836 -1108.143056 [65,] 5652.676431 1219.096836 [66,] 4507.244241 5652.676431 [67,] 5067.530147 4507.244241 [68,] -129.008437 5067.530147 [69,] -5647.575946 -129.008437 [70,] -6376.998375 -5647.575946 [71,] 6883.249698 -6376.998375 [72,] -1714.081818 6883.249698 [73,] -1203.059705 -1714.081818 [74,] 601.044109 -1203.059705 [75,] 116.763730 601.044109 [76,] -2181.666273 116.763730 [77,] 1112.437191 -2181.666273 [78,] 898.706333 1112.437191 [79,] 4716.449009 898.706333 [80,] -1502.288222 4716.449009 [81,] -6562.791997 -1502.288222 [82,] 4528.909035 -6562.791997 [83,] 5629.733375 4528.909035 [84,] -3342.598733 5629.733375 [85,] -1129.494027 -3342.598733 [86,] 343.224771 -1129.494027 [87,] 370.473137 343.224771 [88,] 4587.409258 370.473137 [89,] 2008.606105 4587.409258 [90,] -4355.835739 2008.606105 [91,] 2015.009862 -4355.835739 [92,] -1901.551534 2015.009862 [93,] -2586.271443 -1901.551534 [94,] 3102.501131 -2586.271443 [95,] 3956.183829 3102.501131 [96,] -1004.055800 3956.183829 [97,] 6757.643381 -1004.055800 [98,] 1168.025022 6757.643381 [99,] -616.852456 1168.025022 [100,] 3957.141413 -616.852456 [101,] 2480.395912 3957.141413 [102,] 2825.358597 2480.395912 [103,] 95.819418 2825.358597 [104,] -111.243769 95.819418 [105,] -58.759858 -111.243769 [106,] 2433.437583 -58.759858 [107,] 5262.350904 2433.437583 [108,] -2511.913265 5262.350904 [109,] -948.225350 -2511.913265 [110,] -3311.856704 -948.225350 [111,] 574.580493 -3311.856704 [112,] -4560.254844 574.580493 [113,] -6011.567452 -4560.254844 [114,] 4585.574435 -6011.567452 [115,] -10934.655220 4585.574435 [116,] -2693.507603 -10934.655220 [117,] 3085.279524 -2693.507603 [118,] -1350.344525 3085.279524 [119,] -65.433797 -1350.344525 [120,] 2079.001376 -65.433797 [121,] -227.857450 2079.001376 [122,] 2939.991139 -227.857450 [123,] 2916.506202 2939.991139 [124,] -4038.040476 2916.506202 [125,] -1301.392626 -4038.040476 [126,] 4587.120959 -1301.392626 [127,] -3347.472685 4587.120959 [128,] 1018.543898 -3347.472685 [129,] -265.045778 1018.543898 [130,] 6240.388734 -265.045778 [131,] -12116.447484 6240.388734 [132,] 13673.865239 -12116.447484 [133,] 1052.450680 13673.865239 [134,] 5938.506392 1052.450680 [135,] 1917.980508 5938.506392 [136,] -119.133015 1917.980508 [137,] -1281.547672 -119.133015 [138,] -5444.700466 -1281.547672 [139,] -6849.630290 -5444.700466 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -391.556179 2875.200611 2 2571.886743 -391.556179 3 -702.154822 2571.886743 4 1109.054112 -702.154822 5 2966.498750 1109.054112 6 280.371803 2966.498750 7 6250.704799 280.371803 8 4151.867519 6250.704799 9 7060.995422 4151.867519 10 -4423.193122 7060.995422 11 1191.183608 -4423.193122 12 7.184547 1191.183608 13 1524.742408 7.184547 14 2115.933647 1524.742408 15 796.556696 2115.933647 16 4035.872178 796.556696 17 -1063.559393 4035.872178 18 -3395.758022 -1063.559393 19 6889.043266 -3395.758022 20 3540.016675 6889.043266 21 1177.861932 3540.016675 22 -5421.996515 1177.861932 23 -2566.550682 -5421.996515 24 -2440.039446 -2566.550682 25 -1236.244289 -2440.039446 26 -7059.183320 -1236.244289 27 -2554.488889 -7059.183320 28 -263.988708 -2554.488889 29 -777.515950 -263.988708 30 -5093.087174 -777.515950 31 815.439041 -5093.087174 32 -218.384771 815.439041 33 -1891.670347 -218.384771 34 194.061600 -1891.670347 35 -2230.147264 194.061600 36 -2758.570113 -2230.147264 37 1723.848892 -2758.570113 38 -4702.257417 1723.848892 39 -3392.503131 -4702.257417 40 -1869.693130 -3392.503131 41 -1872.014979 -1869.693130 42 1851.823694 -1872.014979 43 -4403.891636 1851.823694 44 443.679562 -4403.891636 45 -1017.357816 443.679562 46 2159.114483 -1017.357816 47 -5104.984671 2159.114483 48 -3376.898171 -5104.984671 49 -3575.746472 -3376.898171 50 -1343.997331 -3575.746472 51 1681.281587 -1343.997331 52 -1875.797349 1681.281587 53 -1913.016317 -1875.797349 54 -1246.818660 -1913.016317 55 -314.345711 -1246.818660 56 -2598.123318 -314.345711 57 6705.336305 -2598.123318 58 -1085.880030 6705.336305 59 -839.137515 -1085.880030 60 -1487.094426 -839.137515 61 -2346.501888 -1487.094426 62 738.682947 -2346.501888 63 -1108.143056 738.682947 64 1219.096836 -1108.143056 65 5652.676431 1219.096836 66 4507.244241 5652.676431 67 5067.530147 4507.244241 68 -129.008437 5067.530147 69 -5647.575946 -129.008437 70 -6376.998375 -5647.575946 71 6883.249698 -6376.998375 72 -1714.081818 6883.249698 73 -1203.059705 -1714.081818 74 601.044109 -1203.059705 75 116.763730 601.044109 76 -2181.666273 116.763730 77 1112.437191 -2181.666273 78 898.706333 1112.437191 79 4716.449009 898.706333 80 -1502.288222 4716.449009 81 -6562.791997 -1502.288222 82 4528.909035 -6562.791997 83 5629.733375 4528.909035 84 -3342.598733 5629.733375 85 -1129.494027 -3342.598733 86 343.224771 -1129.494027 87 370.473137 343.224771 88 4587.409258 370.473137 89 2008.606105 4587.409258 90 -4355.835739 2008.606105 91 2015.009862 -4355.835739 92 -1901.551534 2015.009862 93 -2586.271443 -1901.551534 94 3102.501131 -2586.271443 95 3956.183829 3102.501131 96 -1004.055800 3956.183829 97 6757.643381 -1004.055800 98 1168.025022 6757.643381 99 -616.852456 1168.025022 100 3957.141413 -616.852456 101 2480.395912 3957.141413 102 2825.358597 2480.395912 103 95.819418 2825.358597 104 -111.243769 95.819418 105 -58.759858 -111.243769 106 2433.437583 -58.759858 107 5262.350904 2433.437583 108 -2511.913265 5262.350904 109 -948.225350 -2511.913265 110 -3311.856704 -948.225350 111 574.580493 -3311.856704 112 -4560.254844 574.580493 113 -6011.567452 -4560.254844 114 4585.574435 -6011.567452 115 -10934.655220 4585.574435 116 -2693.507603 -10934.655220 117 3085.279524 -2693.507603 118 -1350.344525 3085.279524 119 -65.433797 -1350.344525 120 2079.001376 -65.433797 121 -227.857450 2079.001376 122 2939.991139 -227.857450 123 2916.506202 2939.991139 124 -4038.040476 2916.506202 125 -1301.392626 -4038.040476 126 4587.120959 -1301.392626 127 -3347.472685 4587.120959 128 1018.543898 -3347.472685 129 -265.045778 1018.543898 130 6240.388734 -265.045778 131 -12116.447484 6240.388734 132 13673.865239 -12116.447484 133 1052.450680 13673.865239 134 5938.506392 1052.450680 135 1917.980508 5938.506392 136 -119.133015 1917.980508 137 -1281.547672 -119.133015 138 -5444.700466 -1281.547672 139 -6849.630290 -5444.700466 > 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/www/rcomp/tmp/762pi1324338323.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/www/rcomp/tmp/8zkb51324338323.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/www/rcomp/tmp/9ti3m1324338323.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/www/rcomp/tmp/10f8r81324338323.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/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, '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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/11ymsf1324338323.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/1202um1324338323.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/13cd8m1324338323.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/140v061324338323.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/15yppx1324338323.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/16a1341324338324.tab") + } > > try(system("convert tmp/1686y1324338323.ps tmp/1686y1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/2tx441324338323.ps tmp/2tx441324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/3squk1324338323.ps tmp/3squk1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/4gd9f1324338323.ps tmp/4gd9f1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/5maim1324338323.ps tmp/5maim1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/6anne1324338323.ps tmp/6anne1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/762pi1324338323.ps tmp/762pi1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/8zkb51324338323.ps tmp/8zkb51324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/9ti3m1324338323.ps tmp/9ti3m1324338323.png",intern=TRUE)) character(0) > try(system("convert tmp/10f8r81324338323.ps tmp/10f8r81324338323.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.960 0.260 5.231