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(46.8 + ,46.6 + ,39.8 + ,45.5 + ,59.9 + ,47.9 + ,19.9 + ,39.3 + ,28.2 + ,40 + ,47.9 + ,48.3 + ,36.7 + ,45.3 + ,61.6 + ,46.8 + ,19.6 + ,40.3 + ,28.9 + ,41 + ,48.5 + ,51.3 + ,35.4 + ,46.7 + ,62.6 + ,49 + ,19.6 + ,32.4 + ,30 + ,32.6 + ,49.7 + ,48.3 + ,37.1 + ,47.3 + ,62.8 + ,49.6 + ,20.6 + ,32.7 + ,32.8 + ,32.7 + ,48 + ,44.9 + ,37.9 + ,46.5 + ,61.5 + ,48.9 + ,20.1 + ,34.5 + ,33.6 + ,34.6 + ,48.2 + ,43.9 + ,36.8 + ,44.8 + ,60 + ,46.6 + ,19.8 + ,32.4 + ,34 + ,32.3 + ,47.3 + ,43.2 + ,35.8 + ,44.1 + ,58.5 + ,46.1 + ,19.6 + ,33.1 + ,34.3 + ,33.1 + ,46.6 + ,44.6 + ,36.7 + ,43.9 + ,55.7 + ,47.2 + ,19.7 + ,34.9 + ,34.8 + ,34.9 + ,45.6 + ,46.5 + ,34.6 + ,42.3 + ,53.8 + ,45 + ,19.9 + ,34.1 + ,35 + ,34.1 + ,47.7 + ,50.4 + ,33.2 + ,40.9 + ,52.4 + ,43.1 + ,20.1 + ,31.9 + ,34.6 + ,31.7 + ,48.1 + ,50 + ,32.9 + ,39.8 + ,51.2 + ,41.7 + ,20 + ,32.7 + ,34.5 + ,32.6 + ,47.6 + ,47.6 + ,32 + ,38.9 + ,50.1 + ,40.4 + ,20 + ,32.5 + ,34.1 + ,32.4 + ,46.3 + ,45.2 + ,31.6 + 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,96.5 + ,103.9 + ,113.2 + ,141.1 + ,117.4 + ,142.6 + ,132.3 + ,125.6 + ,103.6 + ,103.7 + ,97.7 + ,102.4 + ,115.1 + ,147 + ,109 + ,149.3 + ,128.6 + ,133.7 + ,98.9 + ,101.8 + ,98.2 + ,98 + ,116.1 + ,141.3 + ,105.6 + ,143.5 + ,125.1 + ,132.6 + ,95.9 + ,98 + ,95.4 + ,94.8 + ,109.6 + ,129.6 + ,99 + ,131.4 + ,128.7 + ,132 + ,91.2 + ,93.4 + ,90.4 + ,89.4 + ,107.3 + ,113.3 + ,89.8 + ,114.7 + ,156.1 + ,150.4 + ,98.7 + ,92.3 + ,88.9 + ,89.6 + ,103.4 + ,120.5 + ,90.9 + ,122.3 + ,163.2 + ,155.7 + ,94.5 + ,88.5 + ,86.8 + ,88.2 + ,91.6 + ,131.2 + ,93.6 + ,133.4 + ,159.8 + ,153.4 + ,95.6 + ,92.2 + ,88.1 + ,97 + ,85.7 + ,132.1 + ,91.2 + ,134.6 + ,157.4 + ,141.1 + ,93.8 + ,93 + ,89.6 + ,94.9 + ,92.9 + ,128.3 + ,85.4 + ,130.9) + ,dim=c(10 + ,145) + ,dimnames=list(c('Graan' + ,'Oliezaden' + ,'suiker' + ,'Totaal' + ,'Plantaardig' + ,'Ijzererts' + ,'schroot' + ,'Totaal' + ,'Steenkool' + ,'aardolie') + ,1:145)) > y <- array(NA,dim=c(10,145),dimnames=list(c('Graan','Oliezaden','suiker','Totaal','Plantaardig','Ijzererts','schroot','Totaal','Steenkool','aardolie'),1:145)) > 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 = '8' > 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 Totaal Graan Oliezaden suiker Totaal Plantaardig Ijzererts schroot 1 39.3 46.8 46.6 39.8 45.5 59.9 47.9 19.9 2 40.3 47.9 48.3 36.7 45.3 61.6 46.8 19.6 3 32.4 48.5 51.3 35.4 46.7 62.6 49.0 19.6 4 32.7 49.7 48.3 37.1 47.3 62.8 49.6 20.6 5 34.5 48.0 44.9 37.9 46.5 61.5 48.9 20.1 6 32.4 48.2 43.9 36.8 44.8 60.0 46.6 19.8 7 33.1 47.3 43.2 35.8 44.1 58.5 46.1 19.6 8 34.9 46.6 44.6 36.7 43.9 55.7 47.2 19.7 9 34.1 45.6 46.5 34.6 42.3 53.8 45.0 19.9 10 31.9 47.7 50.4 33.2 40.9 52.4 43.1 20.1 11 32.7 48.1 50.0 32.9 39.8 51.2 41.7 20.0 12 32.5 47.6 47.6 32.0 38.9 50.1 40.4 20.0 13 27.2 46.3 45.2 31.6 37.8 49.5 38.7 19.9 14 24.3 46.1 46.5 33.8 38.4 49.2 40.1 19.5 15 24.0 46.7 45.2 34.5 38.3 47.8 40.7 19.5 16 24.7 47.1 45.4 34.7 38.9 48.6 41.8 18.9 17 25.6 46.7 44.8 34.8 39.4 49.8 41.9 19.2 18 30.1 46.3 46.7 37.2 40.6 51.2 43.3 19.5 19 32.1 45.9 47.4 37.2 40.3 51.0 42.7 20.0 20 32.3 46.6 48.9 36.2 40.1 50.9 41.9 20.8 21 31.0 49.0 51.1 35.9 40.9 52.3 42.6 21.3 22 32.2 54.1 55.6 37.4 41.0 53.5 42.1 21.6 23 33.2 59.2 55.5 37.2 39.9 53.1 40.2 21.6 24 35.2 63.8 55.0 41.3 40.2 53.6 40.4 21.6 25 34.2 62.5 52.6 43.2 40.3 53.4 40.7 21.5 26 31.0 59.5 54.1 42.1 41.6 54.4 42.8 21.6 27 34.1 56.9 53.9 42.4 41.8 54.7 43.0 21.7 28 37.8 54.4 54.1 44.6 43.2 56.9 43.6 23.7 29 40.6 54.7 55.0 46.0 44.8 59.1 45.1 24.9 30 37.5 53.3 54.4 41.8 45.1 61.4 44.1 25.4 31 31.8 52.9 56.5 41.4 44.3 62.1 42.3 25.3 32 32.4 54.8 59.6 40.7 45.4 63.2 44.2 24.5 33 34.6 52.6 59.1 37.2 45.5 63.1 44.9 23.3 34 35.6 49.1 55.7 38.4 45.6 61.9 45.8 23.4 35 37.0 52.6 54.3 38.7 46.3 61.9 46.7 24.4 36 33.8 53.6 58.9 39.6 46.6 63.1 46.3 25.2 37 36.2 52.7 68.6 37.6 49.2 66.6 49.1 26.2 38 36.6 55.8 71.8 37.0 50.4 67.4 50.9 26.3 39 37.8 57.9 71.8 38.6 51.7 65.9 53.7 27.3 40 39.8 60.6 76.7 41.2 54.7 67.8 56.8 31.8 41 39.7 61.9 79.9 41.2 57.6 69.1 60.2 35.5 42 42.8 65.5 90.4 41.9 58.2 70.0 60.0 38.1 43 43.4 67.5 92.1 40.9 58.0 69.9 60.7 35.5 44 47.8 65.5 88.5 41.2 55.6 70.7 56.7 32.5 45 46.3 62.2 81.8 43.1 56.6 71.2 59.0 31.1 46 48.6 55.5 74.5 42.7 58.2 71.0 60.9 34.4 47 53.1 52.3 58.7 43.3 57.9 69.4 59.9 37.1 48 52.7 52.5 54.6 44.0 58.3 70.1 60.6 36.6 49 59.0 50.8 51.8 44.1 60.1 69.4 64.0 37.9 50 53.9 50.9 52.1 47.3 61.2 69.7 64.3 41.9 51 49.7 51.5 52.8 51.0 60.9 69.3 65.1 39.0 52 54.3 51.1 51.9 50.9 63.9 71.6 65.5 49.3 53 55.9 51.1 52.7 55.1 65.4 73.6 67.4 49.5 54 63.9 54.3 60.8 60.5 67.4 74.8 70.7 49.3 55 64.0 51.9 60.3 57.5 66.1 74.1 68.6 49.2 56 60.7 52.4 61.8 57.6 62.5 70.7 65.2 44.6 57 67.8 53.4 66.6 56.9 61.3 67.8 65.6 41.8 58 70.5 56.0 66.1 54.1 61.7 69.1 65.8 41.5 59 76.6 53.4 60.6 53.3 64.4 69.5 68.9 46.4 60 76.2 53.8 56.2 51.8 65.0 69.6 68.5 50.1 61 71.8 53.8 55.2 53.6 65.8 71.4 70.6 46.1 62 67.8 51.6 55.7 54.8 67.6 70.4 74.1 47.7 63 69.7 54.2 58.0 57.3 71.3 71.1 81.1 47.2 64 76.7 55.7 57.1 65.0 75.5 74.0 85.8 51.9 65 74.2 59.2 56.8 65.3 77.8 75.2 89.3 52.6 66 75.8 59.8 56.1 62.9 78.1 75.0 89.6 53.7 67 84.3 61.6 55.5 63.5 85.0 75.1 102.6 54.8 68 84.9 65.8 57.0 62.1 93.7 78.0 117.7 55.4 69 84.4 64.2 57.0 59.3 87.4 80.0 104.1 55.9 70 89.4 67.0 56.5 61.6 91.8 82.4 111.0 56.8 71 88.5 62.8 54.2 61.5 91.9 82.4 112.2 54.1 72 76.5 65.5 53.9 60.1 90.9 79.7 112.0 53.2 73 71.4 75.2 58.0 59.5 94.5 80.6 118.4 53.7 74 72.1 80.9 64.1 62.7 94.5 80.9 118.4 53.5 75 75.8 83.2 63.4 65.5 96.8 84.1 120.8 53.9 76 66.6 83.7 67.2 63.8 96.6 89.1 116.1 58.4 77 71.7 86.4 72.0 63.8 98.3 90.6 118.0 59.3 78 75.4 85.9 72.1 62.7 101.6 90.7 122.7 63.9 79 80.9 80.4 70.0 62.3 107.7 94.6 132.4 64.0 80 80.7 81.8 73.9 62.4 108.1 95.4 133.7 61.5 81 85.0 87.5 79.1 64.8 102.6 94.1 124.2 60.5 82 91.5 83.7 81.1 66.4 103.0 96.2 123.7 60.8 83 87.7 87.0 81.1 65.1 97.3 95.5 113.2 60.3 84 95.3 99.7 90.3 67.4 96.2 94.3 111.5 61.1 85 102.4 101.4 94.2 68.8 98.5 94.2 115.7 61.3 86 114.2 101.9 100.8 68.6 96.2 95.1 111.0 61.0 87 111.7 115.7 108.4 71.5 92.7 96.6 103.1 61.4 88 113.7 123.2 119.6 75.0 101.3 95.9 107.3 93.6 89 118.8 136.9 128.8 84.3 106.9 94.0 118.9 94.3 90 129.0 146.8 127.9 84.0 112.6 94.9 128.3 97.3 91 136.4 149.6 123.9 79.1 113.2 95.2 126.5 104.6 92 155.0 146.5 125.4 78.8 112.9 95.8 121.7 113.8 93 166.0 157.0 139.5 82.7 112.3 97.9 119.5 113.8 94 168.7 147.9 139.0 85.3 113.2 98.3 121.4 113.1 95 145.5 133.6 117.3 84.5 105.0 93.7 110.3 107.2 96 127.3 128.7 108.1 80.8 96.7 91.7 101.5 91.6 97 91.5 100.8 85.4 70.1 79.2 80.1 78.5 79.7 98 69.0 91.8 82.8 68.2 69.4 71.1 66.8 73.7 99 54.0 89.3 80.0 68.1 63.1 67.1 55.2 77.4 100 56.3 96.7 92.6 72.3 60.1 66.0 55.3 63.9 101 54.2 91.6 88.2 73.1 58.2 62.9 53.1 64.5 102 59.3 93.3 85.2 71.5 59.2 62.9 55.2 64.1 103 63.4 93.3 96.5 74.1 62.6 63.9 61.2 64.5 104 73.3 101.0 109.1 80.3 65.1 66.2 64.1 65.9 105 86.7 100.4 115.6 80.6 69.4 69.5 70.4 66.8 106 81.3 86.9 100.0 81.4 72.3 72.8 73.6 68.7 107 89.6 83.9 101.8 87.4 80.6 78.0 86.2 70.2 108 85.3 80.3 88.8 89.3 80.4 82.2 83.5 70.6 109 92.4 87.7 90.9 93.2 82.6 86.3 85.9 69.6 110 96.8 92.7 95.7 92.8 85.1 90.3 88.6 69.2 111 93.6 95.5 97.7 96.8 89.3 92.2 95.2 70.7 112 97.6 92.0 93.4 100.3 91.8 93.1 99.5 70.7 113 94.2 87.4 89.7 95.6 87.9 92.4 92.2 71.0 114 99.9 86.8 89.7 89.0 93.5 96.0 100.7 72.1 115 106.4 83.7 92.5 87.4 103.7 99.6 106.6 101.7 116 96.0 85.0 90.9 86.7 96.4 96.6 93.6 103.0 117 94.9 81.7 91.7 92.8 93.1 96.3 87.3 103.1 118 94.8 90.9 95.8 98.6 98.0 98.7 90.1 116.5 119 95.9 101.5 99.5 100.8 102.1 100.4 97.1 116.9 120 96.2 113.8 101.5 105.5 104.9 102.0 101.3 117.6 121 103.1 120.1 110.6 107.8 108.6 107.1 109.5 108.3 122 106.9 122.1 119.0 113.7 108.6 108.2 109.2 107.7 123 114.2 132.5 124.5 120.3 110.9 108.6 113.0 108.8 124 118.2 140.0 133.4 126.5 116.5 112.9 118.2 117.1 125 123.9 149.4 133.3 134.8 120.2 116.4 123.1 118.3 126 137.1 144.3 127.8 134.5 118.9 114.1 121.5 118.8 127 146.2 154.4 127.3 133.1 124.7 118.1 123.8 135.8 128 136.4 151.4 127.6 128.8 120.5 115.0 117.8 134.6 129 133.2 145.5 126.3 127.1 119.9 116.0 116.0 134.8 130 135.9 136.8 125.1 129.1 120.5 114.1 119.1 132.7 131 127.1 146.6 124.7 128.4 117.3 113.5 112.1 135.7 132 128.5 145.1 121.9 126.5 113.1 110.0 105.4 136.2 133 126.6 133.6 111.2 117.1 104.0 105.1 97.0 120.0 134 132.6 131.4 108.5 114.2 99.2 97.7 95.2 111.3 135 130.9 127.5 105.9 109.1 97.6 94.0 94.1 111.0 136 134.1 130.1 111.9 110.3 100.9 93.8 99.8 113.0 137 141.1 131.1 116.6 109.2 103.8 96.5 103.9 113.2 138 147.0 132.3 125.6 103.6 103.7 97.7 102.4 115.1 139 141.3 128.6 133.7 98.9 101.8 98.2 98.0 116.1 140 129.6 125.1 132.6 95.9 98.0 95.4 94.8 109.6 141 113.3 128.7 132.0 91.2 93.4 90.4 89.4 107.3 142 120.5 156.1 150.4 98.7 92.3 88.9 89.6 103.4 143 131.2 163.2 155.7 94.5 88.5 86.8 88.2 91.6 144 132.1 159.8 153.4 95.6 92.2 88.1 97.0 85.7 145 128.3 157.4 141.1 93.8 93.0 89.6 94.9 92.9 Steenkool aardolie 1 28.2 40.0 2 28.9 41.0 3 30.0 32.6 4 32.8 32.7 5 33.6 34.6 6 34.0 32.3 7 34.3 33.1 8 34.8 34.9 9 35.0 34.1 10 34.6 31.7 11 34.5 32.6 12 34.1 32.4 13 32.9 26.9 14 32.4 23.8 15 30.2 23.7 16 28.9 24.5 17 29.8 25.3 18 30.1 30.1 19 29.5 32.3 20 28.5 32.5 21 27.9 31.2 22 26.2 32.5 23 24.6 33.8 24 25.1 35.8 25 25.6 34.7 26 27.1 31.2 27 27.3 34.6 28 27.4 38.5 29 27.3 41.4 30 26.8 38.1 31 26.1 32.2 32 25.9 32.8 33 26.7 35.1 34 27.5 36.1 35 28.4 37.5 36 30.0 34.0 37 31.1 36.5 38 33.6 36.8 39 38.3 37.8 40 42.9 39.6 41 44.3 39.4 42 53.0 42.1 43 55.6 42.6 44 58.8 47.1 45 64.4 45.2 46 63.3 47.8 47 58.7 52.8 48 57.4 52.4 49 55.3 59.2 50 53.3 54.0 51 53.2 49.5 52 50.9 54.5 53 48.4 56.3 54 51.8 64.6 55 51.6 64.7 56 52.4 61.2 57 52.9 68.7 58 52.8 71.5 59 48.0 78.3 60 46.3 78.1 61 42.0 73.6 62 38.6 69.6 63 41.3 71.5 64 45.3 78.7 65 49.9 75.7 66 53.8 77.1 67 55.1 86.1 68 52.9 86.8 69 53.5 86.3 70 53.8 91.5 71 52.0 90.7 72 48.2 78.2 73 45.5 73.0 74 45.7 73.7 75 52.5 77.3 76 52.3 67.5 77 54.8 72.7 78 54.7 76.6 79 54.9 82.4 80 54.9 82.3 81 64.2 86.3 82 66.4 93.0 83 69.1 88.8 84 68.3 96.9 85 77.3 103.9 86 89.6 115.7 87 93.0 112.8 88 96.1 114.7 89 131.3 118.0 90 125.3 129.3 91 126.0 137.0 92 138.3 156.0 93 163.0 166.2 94 182.5 167.8 95 164.6 144.3 96 148.8 126.0 97 109.3 90.4 98 93.5 67.5 99 80.2 52.4 100 84.0 54.6 101 75.5 52.9 102 62.4 59.1 103 64.2 63.3 104 64.7 73.8 105 71.0 87.6 106 73.7 81.8 107 72.6 90.7 108 68.1 86.3 109 72.3 93.6 110 78.5 98.0 111 81.9 94.3 112 97.8 97.6 113 93.1 94.2 114 94.2 100.2 115 101.1 106.7 116 101.0 95.7 117 99.7 94.6 118 97.1 94.7 119 91.7 96.2 120 95.0 96.3 121 98.9 103.3 122 109.0 106.8 123 121.9 113.7 124 131.5 117.4 125 128.5 123.6 126 128.4 137.6 127 126.4 147.4 128 123.1 137.2 129 123.0 133.8 130 123.3 136.7 131 123.6 127.3 132 124.9 128.7 133 120.4 127.0 134 114.9 133.7 135 113.4 132.0 136 117.6 135.1 137 117.4 142.6 138 109.0 149.3 139 105.6 143.5 140 99.0 131.4 141 89.8 114.7 142 90.9 122.3 143 93.6 133.4 144 91.2 134.6 145 85.4 130.9 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Graan Oliezaden suiker Plantaardig Ijzererts -4.011e-02 -3.221e-04 8.477e-04 -3.779e-04 2.232e-04 2.681e-04 schroot Steenkool aardolie -7.589e-05 5.737e-02 9.425e-01 Warning messages: 1: In model.matrix.default(mt, mf, contrasts) : the response appeared on the right-hand side and was dropped 2: In model.matrix.default(mt, mf, contrasts) : problem with term 4 in model.matrix: no columns are assigned > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.102289 -0.024779 0.007084 0.023762 0.073605 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -4.011e-02 2.617e-02 -1.533 0.1277 Graan -3.221e-04 4.071e-04 -0.791 0.4302 Oliezaden 8.477e-04 4.070e-04 2.083 0.0391 * suiker -3.779e-04 4.147e-04 -0.911 0.3638 Plantaardig 2.232e-04 7.284e-04 0.306 0.7597 Ijzererts 2.681e-04 3.493e-04 0.767 0.4441 schroot -7.589e-05 4.352e-04 -0.174 0.8618 Steenkool 5.737e-02 2.714e-04 211.343 <2e-16 *** aardolie 9.425e-01 3.188e-04 2956.340 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.03841 on 136 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 1.769e+07 on 8 and 136 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,] 0.4490220 0.89804409 0.55097795 [2,] 0.3261544 0.65230873 0.67384564 [3,] 0.3449533 0.68990663 0.65504668 [4,] 0.2565548 0.51310965 0.74344517 [5,] 0.6787187 0.64256259 0.32128129 [6,] 0.5847864 0.83042710 0.41521355 [7,] 0.5368557 0.92628853 0.46314426 [8,] 0.5504374 0.89912522 0.44956261 [9,] 0.4950921 0.99018421 0.50490789 [10,] 0.4392664 0.87853271 0.56073364 [11,] 0.6829806 0.63403888 0.31701944 [12,] 0.6311209 0.73775814 0.36887907 [13,] 0.5622811 0.87543773 0.43771886 [14,] 0.5003468 0.99930646 0.49965323 [15,] 0.8539684 0.29206312 0.14603156 [16,] 0.8674482 0.26510366 0.13255183 [17,] 0.8560090 0.28798209 0.14399105 [18,] 0.8774607 0.24507855 0.12253927 [19,] 0.8763368 0.24732633 0.12366316 [20,] 0.8432298 0.31354037 0.15677018 [21,] 0.8076820 0.38463594 0.19231797 [22,] 0.7631986 0.47360275 0.23680138 [23,] 0.7150424 0.56991523 0.28495761 [24,] 0.6713832 0.65723356 0.32861678 [25,] 0.6259063 0.74818734 0.37409367 [26,] 0.6198746 0.76025087 0.38012543 [27,] 0.6301762 0.73964759 0.36982380 [28,] 0.5755225 0.84895497 0.42447749 [29,] 0.5239980 0.95200401 0.47600200 [30,] 0.5279558 0.94408840 0.47204420 [31,] 0.4851734 0.97034685 0.51482657 [32,] 0.4295040 0.85900801 0.57049599 [33,] 0.3823761 0.76475225 0.61762387 [34,] 0.6772424 0.64551513 0.32275757 [35,] 0.6659104 0.66817922 0.33408961 [36,] 0.6492189 0.70156217 0.35078109 [37,] 0.6068557 0.78628864 0.39314432 [38,] 0.6846961 0.63060781 0.31530390 [39,] 0.6565488 0.68690244 0.34345122 [40,] 0.6093599 0.78128013 0.39064007 [41,] 0.6323367 0.73532661 0.36766331 [42,] 0.5951692 0.80966159 0.40483079 [43,] 0.5804853 0.83902941 0.41951471 [44,] 0.5311865 0.93762694 0.46881347 [45,] 0.4852486 0.97049716 0.51475142 [46,] 0.5231413 0.95371733 0.47685866 [47,] 0.5153944 0.96921118 0.48460559 [48,] 0.7684767 0.46304669 0.23152334 [49,] 0.7302913 0.53941733 0.26970866 [50,] 0.7165810 0.56683800 0.28341900 [51,] 0.7787385 0.44252298 0.22126149 [52,] 0.8495412 0.30091762 0.15045881 [53,] 0.8319152 0.33616968 0.16808484 [54,] 0.8600626 0.27987471 0.13993735 [55,] 0.8375158 0.32496849 0.16248425 [56,] 0.8856854 0.22862923 0.11431461 [57,] 0.8652449 0.26951020 0.13475510 [58,] 0.9084290 0.18314207 0.09157104 [59,] 0.8989514 0.20209728 0.10104864 [60,] 0.8916947 0.21661051 0.10830525 [61,] 0.8817949 0.23641024 0.11820512 [62,] 0.8634796 0.27304074 0.13652037 [63,] 0.9219459 0.15610815 0.07805407 [64,] 0.9202353 0.15952939 0.07976469 [65,] 0.9034944 0.19301111 0.09650556 [66,] 0.9102582 0.17948358 0.08974179 [67,] 0.9612341 0.07753188 0.03876594 [68,] 0.9564532 0.08709364 0.04354682 [69,] 0.9583780 0.08324406 0.04162203 [70,] 0.9480840 0.10383195 0.05191598 [71,] 0.9343127 0.13137450 0.06568725 [72,] 0.9213171 0.15736585 0.07868292 [73,] 0.9036071 0.19278571 0.09639285 [74,] 0.8941505 0.21169898 0.10584949 [75,] 0.8715296 0.25694086 0.12847043 [76,] 0.8732202 0.25355969 0.12677985 [77,] 0.8530491 0.29390188 0.14695094 [78,] 0.9508561 0.09828775 0.04914387 [79,] 0.9370074 0.12598529 0.06299265 [80,] 0.9203848 0.15923034 0.07961517 [81,] 0.9244998 0.15100037 0.07550019 [82,] 0.9218978 0.15620435 0.07810217 [83,] 0.9152244 0.16955112 0.08477556 [84,] 0.9006235 0.19875307 0.09937654 [85,] 0.8749199 0.25016021 0.12508011 [86,] 0.8445874 0.31082525 0.15541262 [87,] 0.8099971 0.38000587 0.19000293 [88,] 0.7773507 0.44529868 0.22264934 [89,] 0.7443355 0.51132905 0.25566453 [90,] 0.6989518 0.60209635 0.30104818 [91,] 0.6908505 0.61829907 0.30914953 [92,] 0.6534620 0.69307598 0.34653799 [93,] 0.7192655 0.56146890 0.28073445 [94,] 0.6998268 0.60034645 0.30017322 [95,] 0.7470640 0.50587194 0.25293597 [96,] 0.8131750 0.37365004 0.18682502 [97,] 0.8439217 0.31215659 0.15607830 [98,] 0.9617125 0.07657502 0.03828751 [99,] 0.9462050 0.10759004 0.05379502 [100,] 0.9363210 0.12735791 0.06367896 [101,] 0.9526612 0.09467767 0.04733884 [102,] 0.9433759 0.11324815 0.05662407 [103,] 0.9302695 0.13946110 0.06973055 [104,] 0.9064054 0.18718921 0.09359460 [105,] 0.8881758 0.22364849 0.11182425 [106,] 0.8636676 0.27266471 0.13633236 [107,] 0.8468493 0.30630147 0.15315074 [108,] 0.8202288 0.35954231 0.17977115 [109,] 0.8680790 0.26384194 0.13192097 [110,] 0.8508678 0.29826433 0.14913217 [111,] 0.8218861 0.35622781 0.17811390 [112,] 0.8011305 0.39773903 0.19886952 [113,] 0.7354526 0.52909475 0.26454737 [114,] 0.7463538 0.50729240 0.25364620 [115,] 0.6722070 0.65558590 0.32779295 [116,] 0.5757022 0.84859570 0.42429785 [117,] 0.4877531 0.97550619 0.51224691 [118,] 0.3779489 0.75589785 0.62205107 [119,] 0.2892320 0.57846396 0.71076802 [120,] 0.3278472 0.65569433 0.67215284 There were 50 or more warnings (use warnings() to see the first 50) > postscript(file="/var/fisher/rcomp/tmp/10ouc1353080366.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/2nr8r1353080366.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3cu2l1353080366.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4itzx1353080366.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5167p1353080366.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 145 Frequency = 1 1 2 3 4 5 -0.0124632983 0.0024957918 -0.0471043943 0.0014601105 -0.0321416493 6 7 8 9 10 0.0141299160 -0.0567156434 0.0173329898 -0.0418225916 0.0408471156 11 12 13 14 15 -0.0006929208 0.0128848808 -0.0323756754 0.0174417374 -0.0603886610 16 17 18 19 20 -0.0403113531 0.0541895408 0.0113921510 -0.0282079243 0.0395282824 21 22 23 24 25 -0.0024451203 0.0680871577 -0.0631503498 0.0264185505 0.0367963633 26 27 28 29 30 0.0461300028 -0.0705743892 -0.0527775420 0.0187154203 0.0559736009 31 32 33 34 35 -0.0447510145 -0.0018851014 -0.0174350404 -0.0036042703 0.0275018062 36 37 38 39 40 0.0311936166 0.0010690535 -0.0276973096 -0.0388973569 -0.0025322275 41 42 43 44 45 0.0024435508 0.0511275766 0.0291778548 0.0074580581 -0.0185081819 46 47 48 49 50 -0.1022886105 -0.0375759663 0.0174307121 0.0299804380 -0.0530460125 51 52 53 54 55 -0.0053224267 0.0147843322 0.0616351672 0.0387207874 0.0551710578 56 57 58 59 60 0.0083419118 0.0070844221 0.0736052988 0.0428115100 -0.0675040001 61 62 63 64 65 0.0207656028 -0.0153861620 -0.0632996213 -0.0762950228 -0.0122827455 66 67 68 69 70 0.0443892441 -0.0149643341 0.0463810542 -0.0151154745 0.0664549385 71 72 73 74 75 0.0237622007 0.0244215599 -0.0220486124 0.0045067895 -0.0775876559 76 77 78 79 80 -0.0326483842 0.0188627653 0.0471817675 0.0654942228 -0.0437881830 81 82 83 84 85 -0.0462755633 0.0100161414 0.0172100174 0.0266464227 0.0093991778 86 87 88 89 90 -0.0224024642 0.0167669739 0.0438630955 0.0117466824 -0.0931708676 91 92 93 94 95 0.0126892623 -0.0013061454 -0.0389252876 0.0322221938 0.0253142106 96 97 98 99 100 -0.0137587714 0.0199491773 0.0132954842 0.0141162059 0.0150657097 101 102 103 104 105 0.0086795812 0.0184571924 0.0462207432 0.0140479810 0.0379336305 106 107 108 109 110 -0.0426188061 -0.0725817698 0.0430453362 0.0221619915 -0.0848494082 111 112 113 114 115 0.0060620863 -0.0138896761 0.0623113480 0.0384098421 0.0120940363 116 117 118 119 120 -0.0086995710 0.0049749706 -0.0387142485 -0.0438302445 -0.0247792542 121 122 123 124 125 0.0450018918 -0.0376728823 0.0190771711 -0.0234704695 0.0092579621 126 127 128 129 130 0.0236195444 0.0045977199 0.0069618363 0.0160959580 -0.0360135912 131 132 133 134 135 0.0119214755 0.0216067909 -0.0140314246 -0.0114326127 -0.0229822911 136 137 138 139 140 0.0091433695 -0.0540382450 0.0038839858 -0.0431520564 0.0396041713 141 142 143 144 145 0.0097194162 -0.0204797488 0.0588283007 -0.0363413171 -0.0065480545 > postscript(file="/var/fisher/rcomp/tmp/6b07g1353080366.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 = 145 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.0124632983 NA 1 0.0024957918 -0.0124632983 2 -0.0471043943 0.0024957918 3 0.0014601105 -0.0471043943 4 -0.0321416493 0.0014601105 5 0.0141299160 -0.0321416493 6 -0.0567156434 0.0141299160 7 0.0173329898 -0.0567156434 8 -0.0418225916 0.0173329898 9 0.0408471156 -0.0418225916 10 -0.0006929208 0.0408471156 11 0.0128848808 -0.0006929208 12 -0.0323756754 0.0128848808 13 0.0174417374 -0.0323756754 14 -0.0603886610 0.0174417374 15 -0.0403113531 -0.0603886610 16 0.0541895408 -0.0403113531 17 0.0113921510 0.0541895408 18 -0.0282079243 0.0113921510 19 0.0395282824 -0.0282079243 20 -0.0024451203 0.0395282824 21 0.0680871577 -0.0024451203 22 -0.0631503498 0.0680871577 23 0.0264185505 -0.0631503498 24 0.0367963633 0.0264185505 25 0.0461300028 0.0367963633 26 -0.0705743892 0.0461300028 27 -0.0527775420 -0.0705743892 28 0.0187154203 -0.0527775420 29 0.0559736009 0.0187154203 30 -0.0447510145 0.0559736009 31 -0.0018851014 -0.0447510145 32 -0.0174350404 -0.0018851014 33 -0.0036042703 -0.0174350404 34 0.0275018062 -0.0036042703 35 0.0311936166 0.0275018062 36 0.0010690535 0.0311936166 37 -0.0276973096 0.0010690535 38 -0.0388973569 -0.0276973096 39 -0.0025322275 -0.0388973569 40 0.0024435508 -0.0025322275 41 0.0511275766 0.0024435508 42 0.0291778548 0.0511275766 43 0.0074580581 0.0291778548 44 -0.0185081819 0.0074580581 45 -0.1022886105 -0.0185081819 46 -0.0375759663 -0.1022886105 47 0.0174307121 -0.0375759663 48 0.0299804380 0.0174307121 49 -0.0530460125 0.0299804380 50 -0.0053224267 -0.0530460125 51 0.0147843322 -0.0053224267 52 0.0616351672 0.0147843322 53 0.0387207874 0.0616351672 54 0.0551710578 0.0387207874 55 0.0083419118 0.0551710578 56 0.0070844221 0.0083419118 57 0.0736052988 0.0070844221 58 0.0428115100 0.0736052988 59 -0.0675040001 0.0428115100 60 0.0207656028 -0.0675040001 61 -0.0153861620 0.0207656028 62 -0.0632996213 -0.0153861620 63 -0.0762950228 -0.0632996213 64 -0.0122827455 -0.0762950228 65 0.0443892441 -0.0122827455 66 -0.0149643341 0.0443892441 67 0.0463810542 -0.0149643341 68 -0.0151154745 0.0463810542 69 0.0664549385 -0.0151154745 70 0.0237622007 0.0664549385 71 0.0244215599 0.0237622007 72 -0.0220486124 0.0244215599 73 0.0045067895 -0.0220486124 74 -0.0775876559 0.0045067895 75 -0.0326483842 -0.0775876559 76 0.0188627653 -0.0326483842 77 0.0471817675 0.0188627653 78 0.0654942228 0.0471817675 79 -0.0437881830 0.0654942228 80 -0.0462755633 -0.0437881830 81 0.0100161414 -0.0462755633 82 0.0172100174 0.0100161414 83 0.0266464227 0.0172100174 84 0.0093991778 0.0266464227 85 -0.0224024642 0.0093991778 86 0.0167669739 -0.0224024642 87 0.0438630955 0.0167669739 88 0.0117466824 0.0438630955 89 -0.0931708676 0.0117466824 90 0.0126892623 -0.0931708676 91 -0.0013061454 0.0126892623 92 -0.0389252876 -0.0013061454 93 0.0322221938 -0.0389252876 94 0.0253142106 0.0322221938 95 -0.0137587714 0.0253142106 96 0.0199491773 -0.0137587714 97 0.0132954842 0.0199491773 98 0.0141162059 0.0132954842 99 0.0150657097 0.0141162059 100 0.0086795812 0.0150657097 101 0.0184571924 0.0086795812 102 0.0462207432 0.0184571924 103 0.0140479810 0.0462207432 104 0.0379336305 0.0140479810 105 -0.0426188061 0.0379336305 106 -0.0725817698 -0.0426188061 107 0.0430453362 -0.0725817698 108 0.0221619915 0.0430453362 109 -0.0848494082 0.0221619915 110 0.0060620863 -0.0848494082 111 -0.0138896761 0.0060620863 112 0.0623113480 -0.0138896761 113 0.0384098421 0.0623113480 114 0.0120940363 0.0384098421 115 -0.0086995710 0.0120940363 116 0.0049749706 -0.0086995710 117 -0.0387142485 0.0049749706 118 -0.0438302445 -0.0387142485 119 -0.0247792542 -0.0438302445 120 0.0450018918 -0.0247792542 121 -0.0376728823 0.0450018918 122 0.0190771711 -0.0376728823 123 -0.0234704695 0.0190771711 124 0.0092579621 -0.0234704695 125 0.0236195444 0.0092579621 126 0.0045977199 0.0236195444 127 0.0069618363 0.0045977199 128 0.0160959580 0.0069618363 129 -0.0360135912 0.0160959580 130 0.0119214755 -0.0360135912 131 0.0216067909 0.0119214755 132 -0.0140314246 0.0216067909 133 -0.0114326127 -0.0140314246 134 -0.0229822911 -0.0114326127 135 0.0091433695 -0.0229822911 136 -0.0540382450 0.0091433695 137 0.0038839858 -0.0540382450 138 -0.0431520564 0.0038839858 139 0.0396041713 -0.0431520564 140 0.0097194162 0.0396041713 141 -0.0204797488 0.0097194162 142 0.0588283007 -0.0204797488 143 -0.0363413171 0.0588283007 144 -0.0065480545 -0.0363413171 145 NA -0.0065480545 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.0024957918 -0.0124632983 [2,] -0.0471043943 0.0024957918 [3,] 0.0014601105 -0.0471043943 [4,] -0.0321416493 0.0014601105 [5,] 0.0141299160 -0.0321416493 [6,] -0.0567156434 0.0141299160 [7,] 0.0173329898 -0.0567156434 [8,] -0.0418225916 0.0173329898 [9,] 0.0408471156 -0.0418225916 [10,] -0.0006929208 0.0408471156 [11,] 0.0128848808 -0.0006929208 [12,] -0.0323756754 0.0128848808 [13,] 0.0174417374 -0.0323756754 [14,] -0.0603886610 0.0174417374 [15,] -0.0403113531 -0.0603886610 [16,] 0.0541895408 -0.0403113531 [17,] 0.0113921510 0.0541895408 [18,] -0.0282079243 0.0113921510 [19,] 0.0395282824 -0.0282079243 [20,] -0.0024451203 0.0395282824 [21,] 0.0680871577 -0.0024451203 [22,] -0.0631503498 0.0680871577 [23,] 0.0264185505 -0.0631503498 [24,] 0.0367963633 0.0264185505 [25,] 0.0461300028 0.0367963633 [26,] -0.0705743892 0.0461300028 [27,] -0.0527775420 -0.0705743892 [28,] 0.0187154203 -0.0527775420 [29,] 0.0559736009 0.0187154203 [30,] -0.0447510145 0.0559736009 [31,] -0.0018851014 -0.0447510145 [32,] -0.0174350404 -0.0018851014 [33,] -0.0036042703 -0.0174350404 [34,] 0.0275018062 -0.0036042703 [35,] 0.0311936166 0.0275018062 [36,] 0.0010690535 0.0311936166 [37,] -0.0276973096 0.0010690535 [38,] -0.0388973569 -0.0276973096 [39,] -0.0025322275 -0.0388973569 [40,] 0.0024435508 -0.0025322275 [41,] 0.0511275766 0.0024435508 [42,] 0.0291778548 0.0511275766 [43,] 0.0074580581 0.0291778548 [44,] -0.0185081819 0.0074580581 [45,] -0.1022886105 -0.0185081819 [46,] -0.0375759663 -0.1022886105 [47,] 0.0174307121 -0.0375759663 [48,] 0.0299804380 0.0174307121 [49,] -0.0530460125 0.0299804380 [50,] -0.0053224267 -0.0530460125 [51,] 0.0147843322 -0.0053224267 [52,] 0.0616351672 0.0147843322 [53,] 0.0387207874 0.0616351672 [54,] 0.0551710578 0.0387207874 [55,] 0.0083419118 0.0551710578 [56,] 0.0070844221 0.0083419118 [57,] 0.0736052988 0.0070844221 [58,] 0.0428115100 0.0736052988 [59,] -0.0675040001 0.0428115100 [60,] 0.0207656028 -0.0675040001 [61,] -0.0153861620 0.0207656028 [62,] -0.0632996213 -0.0153861620 [63,] -0.0762950228 -0.0632996213 [64,] -0.0122827455 -0.0762950228 [65,] 0.0443892441 -0.0122827455 [66,] -0.0149643341 0.0443892441 [67,] 0.0463810542 -0.0149643341 [68,] -0.0151154745 0.0463810542 [69,] 0.0664549385 -0.0151154745 [70,] 0.0237622007 0.0664549385 [71,] 0.0244215599 0.0237622007 [72,] -0.0220486124 0.0244215599 [73,] 0.0045067895 -0.0220486124 [74,] -0.0775876559 0.0045067895 [75,] -0.0326483842 -0.0775876559 [76,] 0.0188627653 -0.0326483842 [77,] 0.0471817675 0.0188627653 [78,] 0.0654942228 0.0471817675 [79,] -0.0437881830 0.0654942228 [80,] -0.0462755633 -0.0437881830 [81,] 0.0100161414 -0.0462755633 [82,] 0.0172100174 0.0100161414 [83,] 0.0266464227 0.0172100174 [84,] 0.0093991778 0.0266464227 [85,] -0.0224024642 0.0093991778 [86,] 0.0167669739 -0.0224024642 [87,] 0.0438630955 0.0167669739 [88,] 0.0117466824 0.0438630955 [89,] -0.0931708676 0.0117466824 [90,] 0.0126892623 -0.0931708676 [91,] -0.0013061454 0.0126892623 [92,] -0.0389252876 -0.0013061454 [93,] 0.0322221938 -0.0389252876 [94,] 0.0253142106 0.0322221938 [95,] -0.0137587714 0.0253142106 [96,] 0.0199491773 -0.0137587714 [97,] 0.0132954842 0.0199491773 [98,] 0.0141162059 0.0132954842 [99,] 0.0150657097 0.0141162059 [100,] 0.0086795812 0.0150657097 [101,] 0.0184571924 0.0086795812 [102,] 0.0462207432 0.0184571924 [103,] 0.0140479810 0.0462207432 [104,] 0.0379336305 0.0140479810 [105,] -0.0426188061 0.0379336305 [106,] -0.0725817698 -0.0426188061 [107,] 0.0430453362 -0.0725817698 [108,] 0.0221619915 0.0430453362 [109,] -0.0848494082 0.0221619915 [110,] 0.0060620863 -0.0848494082 [111,] -0.0138896761 0.0060620863 [112,] 0.0623113480 -0.0138896761 [113,] 0.0384098421 0.0623113480 [114,] 0.0120940363 0.0384098421 [115,] -0.0086995710 0.0120940363 [116,] 0.0049749706 -0.0086995710 [117,] -0.0387142485 0.0049749706 [118,] -0.0438302445 -0.0387142485 [119,] -0.0247792542 -0.0438302445 [120,] 0.0450018918 -0.0247792542 [121,] -0.0376728823 0.0450018918 [122,] 0.0190771711 -0.0376728823 [123,] -0.0234704695 0.0190771711 [124,] 0.0092579621 -0.0234704695 [125,] 0.0236195444 0.0092579621 [126,] 0.0045977199 0.0236195444 [127,] 0.0069618363 0.0045977199 [128,] 0.0160959580 0.0069618363 [129,] -0.0360135912 0.0160959580 [130,] 0.0119214755 -0.0360135912 [131,] 0.0216067909 0.0119214755 [132,] -0.0140314246 0.0216067909 [133,] -0.0114326127 -0.0140314246 [134,] -0.0229822911 -0.0114326127 [135,] 0.0091433695 -0.0229822911 [136,] -0.0540382450 0.0091433695 [137,] 0.0038839858 -0.0540382450 [138,] -0.0431520564 0.0038839858 [139,] 0.0396041713 -0.0431520564 [140,] 0.0097194162 0.0396041713 [141,] -0.0204797488 0.0097194162 [142,] 0.0588283007 -0.0204797488 [143,] -0.0363413171 0.0588283007 [144,] -0.0065480545 -0.0363413171 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.0024957918 -0.0124632983 2 -0.0471043943 0.0024957918 3 0.0014601105 -0.0471043943 4 -0.0321416493 0.0014601105 5 0.0141299160 -0.0321416493 6 -0.0567156434 0.0141299160 7 0.0173329898 -0.0567156434 8 -0.0418225916 0.0173329898 9 0.0408471156 -0.0418225916 10 -0.0006929208 0.0408471156 11 0.0128848808 -0.0006929208 12 -0.0323756754 0.0128848808 13 0.0174417374 -0.0323756754 14 -0.0603886610 0.0174417374 15 -0.0403113531 -0.0603886610 16 0.0541895408 -0.0403113531 17 0.0113921510 0.0541895408 18 -0.0282079243 0.0113921510 19 0.0395282824 -0.0282079243 20 -0.0024451203 0.0395282824 21 0.0680871577 -0.0024451203 22 -0.0631503498 0.0680871577 23 0.0264185505 -0.0631503498 24 0.0367963633 0.0264185505 25 0.0461300028 0.0367963633 26 -0.0705743892 0.0461300028 27 -0.0527775420 -0.0705743892 28 0.0187154203 -0.0527775420 29 0.0559736009 0.0187154203 30 -0.0447510145 0.0559736009 31 -0.0018851014 -0.0447510145 32 -0.0174350404 -0.0018851014 33 -0.0036042703 -0.0174350404 34 0.0275018062 -0.0036042703 35 0.0311936166 0.0275018062 36 0.0010690535 0.0311936166 37 -0.0276973096 0.0010690535 38 -0.0388973569 -0.0276973096 39 -0.0025322275 -0.0388973569 40 0.0024435508 -0.0025322275 41 0.0511275766 0.0024435508 42 0.0291778548 0.0511275766 43 0.0074580581 0.0291778548 44 -0.0185081819 0.0074580581 45 -0.1022886105 -0.0185081819 46 -0.0375759663 -0.1022886105 47 0.0174307121 -0.0375759663 48 0.0299804380 0.0174307121 49 -0.0530460125 0.0299804380 50 -0.0053224267 -0.0530460125 51 0.0147843322 -0.0053224267 52 0.0616351672 0.0147843322 53 0.0387207874 0.0616351672 54 0.0551710578 0.0387207874 55 0.0083419118 0.0551710578 56 0.0070844221 0.0083419118 57 0.0736052988 0.0070844221 58 0.0428115100 0.0736052988 59 -0.0675040001 0.0428115100 60 0.0207656028 -0.0675040001 61 -0.0153861620 0.0207656028 62 -0.0632996213 -0.0153861620 63 -0.0762950228 -0.0632996213 64 -0.0122827455 -0.0762950228 65 0.0443892441 -0.0122827455 66 -0.0149643341 0.0443892441 67 0.0463810542 -0.0149643341 68 -0.0151154745 0.0463810542 69 0.0664549385 -0.0151154745 70 0.0237622007 0.0664549385 71 0.0244215599 0.0237622007 72 -0.0220486124 0.0244215599 73 0.0045067895 -0.0220486124 74 -0.0775876559 0.0045067895 75 -0.0326483842 -0.0775876559 76 0.0188627653 -0.0326483842 77 0.0471817675 0.0188627653 78 0.0654942228 0.0471817675 79 -0.0437881830 0.0654942228 80 -0.0462755633 -0.0437881830 81 0.0100161414 -0.0462755633 82 0.0172100174 0.0100161414 83 0.0266464227 0.0172100174 84 0.0093991778 0.0266464227 85 -0.0224024642 0.0093991778 86 0.0167669739 -0.0224024642 87 0.0438630955 0.0167669739 88 0.0117466824 0.0438630955 89 -0.0931708676 0.0117466824 90 0.0126892623 -0.0931708676 91 -0.0013061454 0.0126892623 92 -0.0389252876 -0.0013061454 93 0.0322221938 -0.0389252876 94 0.0253142106 0.0322221938 95 -0.0137587714 0.0253142106 96 0.0199491773 -0.0137587714 97 0.0132954842 0.0199491773 98 0.0141162059 0.0132954842 99 0.0150657097 0.0141162059 100 0.0086795812 0.0150657097 101 0.0184571924 0.0086795812 102 0.0462207432 0.0184571924 103 0.0140479810 0.0462207432 104 0.0379336305 0.0140479810 105 -0.0426188061 0.0379336305 106 -0.0725817698 -0.0426188061 107 0.0430453362 -0.0725817698 108 0.0221619915 0.0430453362 109 -0.0848494082 0.0221619915 110 0.0060620863 -0.0848494082 111 -0.0138896761 0.0060620863 112 0.0623113480 -0.0138896761 113 0.0384098421 0.0623113480 114 0.0120940363 0.0384098421 115 -0.0086995710 0.0120940363 116 0.0049749706 -0.0086995710 117 -0.0387142485 0.0049749706 118 -0.0438302445 -0.0387142485 119 -0.0247792542 -0.0438302445 120 0.0450018918 -0.0247792542 121 -0.0376728823 0.0450018918 122 0.0190771711 -0.0376728823 123 -0.0234704695 0.0190771711 124 0.0092579621 -0.0234704695 125 0.0236195444 0.0092579621 126 0.0045977199 0.0236195444 127 0.0069618363 0.0045977199 128 0.0160959580 0.0069618363 129 -0.0360135912 0.0160959580 130 0.0119214755 -0.0360135912 131 0.0216067909 0.0119214755 132 -0.0140314246 0.0216067909 133 -0.0114326127 -0.0140314246 134 -0.0229822911 -0.0114326127 135 0.0091433695 -0.0229822911 136 -0.0540382450 0.0091433695 137 0.0038839858 -0.0540382450 138 -0.0431520564 0.0038839858 139 0.0396041713 -0.0431520564 140 0.0097194162 0.0396041713 141 -0.0204797488 0.0097194162 142 0.0588283007 -0.0204797488 143 -0.0363413171 0.0588283007 144 -0.0065480545 -0.0363413171 > 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/7b0n01353080366.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/82apb1353080366.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/9as871353080366.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') Warning messages: 1: In model.matrix.default(object, data = list(Totaal = c(39.3, 40.3, : the response appeared on the right-hand side and was dropped 2: In model.matrix.default(object, data = list(Totaal = c(39.3, 40.3, : problem with term 4 in model.matrix: no columns are assigned > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/10km5x1353080366.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