R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(87.28 + ,255 + ,87.28 + ,280.2 + ,87.09 + ,299.9 + ,86.92 + ,339.2 + ,87.59 + ,374.2 + ,90.72 + ,393.5 + ,90.69 + ,389.2 + ,90.3 + ,381.7 + ,89.55 + ,375.2 + ,88.94 + ,369 + ,88.41 + ,357.4 + ,87.82 + ,352.1 + ,87.07 + ,346.5 + ,86.82 + ,342.9 + ,86.4 + ,340.3 + ,86.02 + ,328.3 + ,85.66 + ,322.9 + ,85.32 + ,314.3 + ,85 + ,308.9 + ,84.67 + ,294 + ,83.94 + ,285.6 + ,82.83 + ,281.2 + ,81.95 + ,280.3 + ,81.19 + ,278.8 + ,80.48 + ,274.5 + ,78.86 + ,270.4 + ,69.47 + ,263.4 + ,68.77 + ,259.9 + ,70.06 + ,258 + ,73.95 + ,262.7 + ,75.8 + ,284.7 + ,77.79 + ,311.3 + ,81.57 + ,322.1 + ,83.07 + ,327 + ,84.34 + ,331.3 + ,85.1 + ,333.3 + ,85.25 + ,321.4 + ,84.26 + ,327 + ,83.63 + ,320 + ,86.44 + ,314.7 + ,85.3 + ,316.7 + ,84.1 + ,314.4 + ,83.36 + ,321.3 + ,82.48 + ,318.2 + ,81.58 + ,307.2 + ,80.47 + ,301.3 + ,79.34 + ,287.5 + ,82.13 + ,277.7 + ,81.69 + ,274.4 + ,80.7 + ,258.8 + ,79.88 + ,253.3 + ,79.16 + ,251 + ,78.38 + ,248.4 + ,77.42 + ,249.5 + ,76.47 + ,246.1 + ,75.46 + ,244.5 + ,74.48 + ,243.6 + ,78.27 + ,244 + ,80.7 + ,240.8 + ,79.91 + ,249.8 + ,78.75 + ,248 + ,77.78 + ,259.4 + ,81.14 + ,260.5 + ,81.08 + ,260.8 + ,80.03 + ,261.3 + ,78.91 + ,259.5 + ,78.01 + ,256.6 + ,76.9 + ,257.9 + ,75.97 + ,256.5 + ,81.93 + ,254.2 + ,80.27 + ,253.3 + ,78.67 + ,253.8 + ,77.42 + ,255.5 + ,76.16 + ,257.1 + ,74.7 + ,257.3 + ,76.39 + ,253.2 + ,76.04 + ,252.8 + ,74.65 + ,252 + ,73.29 + ,250.7 + ,71.79 + ,252.2 + ,74.39 + ,250 + ,74.91 + ,251 + ,74.54 + ,253.4 + ,73.08 + ,251.2 + ,72.75 + ,255.6 + ,71.32 + ,261.1 + ,70.38 + ,258.9 + ,70.35 + ,259.9 + ,70.01 + ,261.2 + ,69.36 + ,264.7 + ,67.77 + ,267.1 + ,69.26 + ,266.4 + ,69.8 + ,267.7 + ,68.38 + ,268.6 + ,67.62 + ,267.5 + ,68.39 + ,268.5 + ,66.95 + ,268.5 + ,65.21 + ,270.5 + ,66.64 + ,270.9 + ,63.45 + ,270.1 + ,60.66 + ,269.3 + ,62.34 + ,269.8 + ,60.32 + ,270.1 + ,58.64 + ,264.9 + ,60.46 + ,263.7 + ,58.59 + ,264.8 + ,61.87 + ,263.7 + ,61.85 + ,255.9 + ,67.44 + ,276.2 + ,77.06 + ,360.1 + ,91.74 + ,380.5 + ,93.15 + ,373.7 + ,94.15 + ,369.8 + ,93.11 + ,366.6 + ,91.51 + ,359.3 + ,89.96 + ,345.8 + ,88.16 + ,326.2 + ,86.98 + ,324.5 + ,88.03 + ,328.1 + ,86.24 + ,327.5 + ,84.65 + ,324.4 + ,83.23 + ,316.5 + ,81.7 + ,310.9 + ,80.25 + ,301.5 + ,78.8 + ,291.7 + ,77.51 + ,290.4 + ,76.2 + ,287.4 + ,75.04 + ,277.7 + ,74 + ,281.6 + ,75.49 + ,288 + ,77.14 + ,276 + ,76.15 + ,272.9 + ,76.27 + ,283 + ,78.19 + ,283.3 + ,76.49 + ,276.8 + ,77.31 + ,284.5 + ,76.65 + ,282.7 + ,74.99 + ,281.2 + ,73.51 + ,287.4 + ,72.07 + ,283.1 + ,70.59 + ,284 + ,71.96 + ,285.5 + ,76.29 + ,289.2 + ,74.86 + ,292.5 + ,74.93 + ,296.4 + ,71.9 + ,305.2 + ,71.01 + ,303.9 + ,77.47 + ,311.5 + ,75.78 + ,316.3 + ,76.6 + ,316.7 + ,76.07 + ,322.5 + ,74.57 + ,317.1 + ,73.02 + ,309.8 + ,72.65 + ,303.8 + ,73.16 + ,290.3 + ,71.53 + ,293.7 + ,69.78 + ,291.7 + ,67.98 + ,296.5 + ,69.96 + ,289.1 + ,72.16 + ,288.5 + ,70.47 + ,293.8 + ,68.86 + ,297.7 + ,67.37 + ,305.4 + ,65.87 + ,302.7 + ,72.16 + ,302.5 + ,71.34 + ,303 + ,69.93 + ,294.5 + ,68.44 + ,294.1 + ,67.16 + ,294.5 + ,66.01 + ,297.1 + ,67.25 + ,289.4 + ,70.91 + ,292.4 + ,69.75 + ,287.9 + ,68.59 + ,286.6 + ,67.48 + ,280.5 + ,66.31 + ,272.4 + ,64.81 + ,269.2 + ,66.58 + ,270.6 + ,65.97 + ,267.3 + ,64.7 + ,262.5 + ,64.7 + ,266.8 + ,60.94 + ,268.8 + ,59.08 + ,263.1 + ,58.42 + ,261.2 + ,57.77 + ,266 + ,57.11 + ,262.5 + ,53.31 + ,265.2 + ,49.96 + ,261.3 + ,49.4 + ,253.7 + ,48.84 + ,249.2 + ,48.3 + ,239.1 + ,47.74 + ,236.4 + ,47.24 + ,235.2 + ,46.76 + ,245.2 + ,46.29 + ,246.2 + ,48.9 + ,247.7 + ,49.23 + ,251.4 + ,48.53 + ,253.3 + ,48.03 + ,254.8 + ,54.34 + ,250 + ,53.79 + ,249.3 + ,53.24 + ,241.5 + ,52.96 + ,243.3 + ,52.17 + ,248 + ,51.7 + ,253 + ,58.55 + ,252.9 + ,78.2 + ,251.5 + ,77.03 + ,251.6 + ,76.19 + ,253.5 + ,77.15 + ,259.8 + ,75.87 + ,334.1 + ,95.47 + ,448 + ,109.67 + ,445.8 + ,112.28 + ,445 + ,112.01 + ,448.2 + ,107.93 + ,438.2 + ,105.96 + ,439.8 + ,105.06 + ,423.4 + ,102.98 + ,410.8 + ,102.2 + ,408.4 + ,105.23 + ,406.7 + ,101.85 + ,405.9 + ,99.89 + ,402.7 + ,96.23 + ,405.1 + ,94.76 + ,399.6 + ,91.51 + ,386.5 + ,91.63 + ,381.4 + ,91.54 + ,375.2 + ,85.23 + ,357.7 + ,87.83 + ,359 + ,87.38 + ,355 + ,84.44 + ,352.7 + ,85.19 + ,344.4 + ,84.03 + ,343.8 + ,86.73 + ,338 + ,102.52 + ,339 + ,104.45 + ,333.3 + ,106.98 + ,334.4 + ,107.02 + ,328.3 + ,99.26 + ,330.7 + ,94.45 + ,330 + ,113.44 + ,331.6 + ,157.33 + ,351.2 + ,147.38 + ,389.4 + ,171.89 + ,410.9 + ,171.95 + ,442.8 + ,132.71 + ,462.8 + ,126.02 + ,466.9 + ,121.18 + ,461.7 + ,115.45 + ,439.2 + ,110.48 + ,430.3 + ,117.85 + ,416.1 + ,117.63 + ,402.5 + ,124.65 + ,397.3 + ,109.59 + ,403.3 + ,111.27 + ,395.9 + ,99.78 + ,387.8 + ,98.21 + ,378.6 + ,99.2 + ,377.1 + ,97.97 + ,370.4 + ,89.55 + ,362 + ,87.91 + ,350.3 + ,93.34 + ,348.2 + ,94.42 + ,344.6 + ,93.2 + ,343.5 + ,90.29 + ,342.8 + ,91.46 + ,347.6 + ,89.98 + ,346.6 + ,88.35 + ,349.5 + ,88.41 + ,342.1 + ,82.44 + ,342 + ,79.89 + ,342.8 + ,75.69 + ,339.3 + ,75.66 + ,348.2 + ,84.5 + ,333.7 + ,96.73 + ,334.7 + ,87.48 + ,354 + ,82.39 + ,367.7 + ,83.48 + ,363.3 + ,79.31 + ,358.4 + ,78.16 + ,353.1 + ,72.77 + ,343.1 + ,72.45 + ,344.6 + ,68.46 + ,344.4 + ,67.62 + ,333.9 + ,68.76 + ,331.7 + ,70.07 + ,324.3 + ,68.55 + ,321.2 + ,65.3 + ,322.4 + ,58.96 + ,321.7 + ,59.17 + ,320.5 + ,62.37 + ,312.8 + ,66.28 + ,309.7 + ,55.62 + ,315.6 + ,55.23 + ,309.7 + ,55.85 + ,304.6 + ,56.75 + ,302.5 + ,50.89 + ,301.5 + ,53.88 + ,298.8 + ,52.95 + ,291.3 + ,55.08 + ,293.6 + ,53.61 + ,294.6 + ,58.78 + ,285.9 + ,61.85 + ,297.6 + ,55.91 + ,301.1 + ,53.32 + ,293.8 + ,46.41 + ,297.7 + ,44.57 + ,292.9 + ,50 + ,292.1 + ,50 + ,287.2 + ,53.36 + ,288.2 + ,46.23 + ,283.8 + ,50.45 + ,299.9 + ,49.07 + ,292.4 + ,45.85 + ,293.3 + ,48.45 + ,300.8 + ,49.96 + ,293.7 + ,46.53 + ,293.1 + ,50.51 + ,294.4 + ,47.58 + ,292.1 + ,48.05 + ,291.9 + ,46.84 + ,282.5 + ,47.67 + ,277.9 + ,49.16 + ,287.5 + ,55.54 + ,289.2 + ,55.82 + ,285.6 + ,58.22 + ,293.2 + ,56.19 + ,290.8 + ,57.77 + ,283.1 + ,63.19 + ,275 + ,54.76 + ,287.8 + ,55.74 + ,287.8 + ,62.54 + ,287.4 + ,61.39 + ,284 + ,69.6 + ,277.8 + ,79.23 + ,277.6 + ,80 + ,304.9 + ,93.68 + ,294 + ,107.63 + ,300.9 + ,100.18 + ,324 + ,97.3 + ,332.9 + ,90.45 + ,341.6 + ,80.64 + ,333.4 + ,80.58 + ,348.2 + ,75.82 + ,344.7 + ,85.59 + ,344.7 + ,89.35 + ,329.3 + ,89.42 + ,323.5 + ,104.73 + ,323.2 + ,95.32 + ,317.4 + ,89.27 + ,330.1 + ,90.44 + ,329.2 + ,86.97 + ,334.9 + ,79.98 + ,315.8 + ,81.22 + ,315.4 + ,87.35 + ,319.6 + ,83.64 + ,317.3 + ,82.22 + ,313.8 + ,94.4 + ,315.8 + ,102.18 + ,311.3) + ,dim=c(2 + ,360) + ,dimnames=list(c('Xt' + ,'Yt') + ,1:360)) > y <- array(NA,dim=c(2,360),dimnames=list(c('Xt','Yt'),1:360)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > #'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 > 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 Xt Yt t 1 87.28 255.0 1 2 87.28 280.2 2 3 87.09 299.9 3 4 86.92 339.2 4 5 87.59 374.2 5 6 90.72 393.5 6 7 90.69 389.2 7 8 90.30 381.7 8 9 89.55 375.2 9 10 88.94 369.0 10 11 88.41 357.4 11 12 87.82 352.1 12 13 87.07 346.5 13 14 86.82 342.9 14 15 86.40 340.3 15 16 86.02 328.3 16 17 85.66 322.9 17 18 85.32 314.3 18 19 85.00 308.9 19 20 84.67 294.0 20 21 83.94 285.6 21 22 82.83 281.2 22 23 81.95 280.3 23 24 81.19 278.8 24 25 80.48 274.5 25 26 78.86 270.4 26 27 69.47 263.4 27 28 68.77 259.9 28 29 70.06 258.0 29 30 73.95 262.7 30 31 75.80 284.7 31 32 77.79 311.3 32 33 81.57 322.1 33 34 83.07 327.0 34 35 84.34 331.3 35 36 85.10 333.3 36 37 85.25 321.4 37 38 84.26 327.0 38 39 83.63 320.0 39 40 86.44 314.7 40 41 85.30 316.7 41 42 84.10 314.4 42 43 83.36 321.3 43 44 82.48 318.2 44 45 81.58 307.2 45 46 80.47 301.3 46 47 79.34 287.5 47 48 82.13 277.7 48 49 81.69 274.4 49 50 80.70 258.8 50 51 79.88 253.3 51 52 79.16 251.0 52 53 78.38 248.4 53 54 77.42 249.5 54 55 76.47 246.1 55 56 75.46 244.5 56 57 74.48 243.6 57 58 78.27 244.0 58 59 80.70 240.8 59 60 79.91 249.8 60 61 78.75 248.0 61 62 77.78 259.4 62 63 81.14 260.5 63 64 81.08 260.8 64 65 80.03 261.3 65 66 78.91 259.5 66 67 78.01 256.6 67 68 76.90 257.9 68 69 75.97 256.5 69 70 81.93 254.2 70 71 80.27 253.3 71 72 78.67 253.8 72 73 77.42 255.5 73 74 76.16 257.1 74 75 74.70 257.3 75 76 76.39 253.2 76 77 76.04 252.8 77 78 74.65 252.0 78 79 73.29 250.7 79 80 71.79 252.2 80 81 74.39 250.0 81 82 74.91 251.0 82 83 74.54 253.4 83 84 73.08 251.2 84 85 72.75 255.6 85 86 71.32 261.1 86 87 70.38 258.9 87 88 70.35 259.9 88 89 70.01 261.2 89 90 69.36 264.7 90 91 67.77 267.1 91 92 69.26 266.4 92 93 69.80 267.7 93 94 68.38 268.6 94 95 67.62 267.5 95 96 68.39 268.5 96 97 66.95 268.5 97 98 65.21 270.5 98 99 66.64 270.9 99 100 63.45 270.1 100 101 60.66 269.3 101 102 62.34 269.8 102 103 60.32 270.1 103 104 58.64 264.9 104 105 60.46 263.7 105 106 58.59 264.8 106 107 61.87 263.7 107 108 61.85 255.9 108 109 67.44 276.2 109 110 77.06 360.1 110 111 91.74 380.5 111 112 93.15 373.7 112 113 94.15 369.8 113 114 93.11 366.6 114 115 91.51 359.3 115 116 89.96 345.8 116 117 88.16 326.2 117 118 86.98 324.5 118 119 88.03 328.1 119 120 86.24 327.5 120 121 84.65 324.4 121 122 83.23 316.5 122 123 81.70 310.9 123 124 80.25 301.5 124 125 78.80 291.7 125 126 77.51 290.4 126 127 76.20 287.4 127 128 75.04 277.7 128 129 74.00 281.6 129 130 75.49 288.0 130 131 77.14 276.0 131 132 76.15 272.9 132 133 76.27 283.0 133 134 78.19 283.3 134 135 76.49 276.8 135 136 77.31 284.5 136 137 76.65 282.7 137 138 74.99 281.2 138 139 73.51 287.4 139 140 72.07 283.1 140 141 70.59 284.0 141 142 71.96 285.5 142 143 76.29 289.2 143 144 74.86 292.5 144 145 74.93 296.4 145 146 71.90 305.2 146 147 71.01 303.9 147 148 77.47 311.5 148 149 75.78 316.3 149 150 76.60 316.7 150 151 76.07 322.5 151 152 74.57 317.1 152 153 73.02 309.8 153 154 72.65 303.8 154 155 73.16 290.3 155 156 71.53 293.7 156 157 69.78 291.7 157 158 67.98 296.5 158 159 69.96 289.1 159 160 72.16 288.5 160 161 70.47 293.8 161 162 68.86 297.7 162 163 67.37 305.4 163 164 65.87 302.7 164 165 72.16 302.5 165 166 71.34 303.0 166 167 69.93 294.5 167 168 68.44 294.1 168 169 67.16 294.5 169 170 66.01 297.1 170 171 67.25 289.4 171 172 70.91 292.4 172 173 69.75 287.9 173 174 68.59 286.6 174 175 67.48 280.5 175 176 66.31 272.4 176 177 64.81 269.2 177 178 66.58 270.6 178 179 65.97 267.3 179 180 64.70 262.5 180 181 64.70 266.8 181 182 60.94 268.8 182 183 59.08 263.1 183 184 58.42 261.2 184 185 57.77 266.0 185 186 57.11 262.5 186 187 53.31 265.2 187 188 49.96 261.3 188 189 49.40 253.7 189 190 48.84 249.2 190 191 48.30 239.1 191 192 47.74 236.4 192 193 47.24 235.2 193 194 46.76 245.2 194 195 46.29 246.2 195 196 48.90 247.7 196 197 49.23 251.4 197 198 48.53 253.3 198 199 48.03 254.8 199 200 54.34 250.0 200 201 53.79 249.3 201 202 53.24 241.5 202 203 52.96 243.3 203 204 52.17 248.0 204 205 51.70 253.0 205 206 58.55 252.9 206 207 78.20 251.5 207 208 77.03 251.6 208 209 76.19 253.5 209 210 77.15 259.8 210 211 75.87 334.1 211 212 95.47 448.0 212 213 109.67 445.8 213 214 112.28 445.0 214 215 112.01 448.2 215 216 107.93 438.2 216 217 105.96 439.8 217 218 105.06 423.4 218 219 102.98 410.8 219 220 102.20 408.4 220 221 105.23 406.7 221 222 101.85 405.9 222 223 99.89 402.7 223 224 96.23 405.1 224 225 94.76 399.6 225 226 91.51 386.5 226 227 91.63 381.4 227 228 91.54 375.2 228 229 85.23 357.7 229 230 87.83 359.0 230 231 87.38 355.0 231 232 84.44 352.7 232 233 85.19 344.4 233 234 84.03 343.8 234 235 86.73 338.0 235 236 102.52 339.0 236 237 104.45 333.3 237 238 106.98 334.4 238 239 107.02 328.3 239 240 99.26 330.7 240 241 94.45 330.0 241 242 113.44 331.6 242 243 157.33 351.2 243 244 147.38 389.4 244 245 171.89 410.9 245 246 171.95 442.8 246 247 132.71 462.8 247 248 126.02 466.9 248 249 121.18 461.7 249 250 115.45 439.2 250 251 110.48 430.3 251 252 117.85 416.1 252 253 117.63 402.5 253 254 124.65 397.3 254 255 109.59 403.3 255 256 111.27 395.9 256 257 99.78 387.8 257 258 98.21 378.6 258 259 99.20 377.1 259 260 97.97 370.4 260 261 89.55 362.0 261 262 87.91 350.3 262 263 93.34 348.2 263 264 94.42 344.6 264 265 93.20 343.5 265 266 90.29 342.8 266 267 91.46 347.6 267 268 89.98 346.6 268 269 88.35 349.5 269 270 88.41 342.1 270 271 82.44 342.0 271 272 79.89 342.8 272 273 75.69 339.3 273 274 75.66 348.2 274 275 84.50 333.7 275 276 96.73 334.7 276 277 87.48 354.0 277 278 82.39 367.7 278 279 83.48 363.3 279 280 79.31 358.4 280 281 78.16 353.1 281 282 72.77 343.1 282 283 72.45 344.6 283 284 68.46 344.4 284 285 67.62 333.9 285 286 68.76 331.7 286 287 70.07 324.3 287 288 68.55 321.2 288 289 65.30 322.4 289 290 58.96 321.7 290 291 59.17 320.5 291 292 62.37 312.8 292 293 66.28 309.7 293 294 55.62 315.6 294 295 55.23 309.7 295 296 55.85 304.6 296 297 56.75 302.5 297 298 50.89 301.5 298 299 53.88 298.8 299 300 52.95 291.3 300 301 55.08 293.6 301 302 53.61 294.6 302 303 58.78 285.9 303 304 61.85 297.6 304 305 55.91 301.1 305 306 53.32 293.8 306 307 46.41 297.7 307 308 44.57 292.9 308 309 50.00 292.1 309 310 50.00 287.2 310 311 53.36 288.2 311 312 46.23 283.8 312 313 50.45 299.9 313 314 49.07 292.4 314 315 45.85 293.3 315 316 48.45 300.8 316 317 49.96 293.7 317 318 46.53 293.1 318 319 50.51 294.4 319 320 47.58 292.1 320 321 48.05 291.9 321 322 46.84 282.5 322 323 47.67 277.9 323 324 49.16 287.5 324 325 55.54 289.2 325 326 55.82 285.6 326 327 58.22 293.2 327 328 56.19 290.8 328 329 57.77 283.1 329 330 63.19 275.0 330 331 54.76 287.8 331 332 55.74 287.8 332 333 62.54 287.4 333 334 61.39 284.0 334 335 69.60 277.8 335 336 79.23 277.6 336 337 80.00 304.9 337 338 93.68 294.0 338 339 107.63 300.9 339 340 100.18 324.0 340 341 97.30 332.9 341 342 90.45 341.6 342 343 80.64 333.4 343 344 80.58 348.2 344 345 75.82 344.7 345 346 85.59 344.7 346 347 89.35 329.3 347 348 89.42 323.5 348 349 104.73 323.2 349 350 95.32 317.4 350 351 89.27 330.1 351 352 90.44 329.2 352 353 86.97 334.9 353 354 79.98 315.8 354 355 81.22 315.4 355 356 87.35 319.6 356 357 83.64 317.3 357 358 82.22 313.8 358 359 94.40 315.8 359 360 102.18 311.3 360 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Yt t -6.6003 0.3013 -0.0485 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -22.610 -7.585 -1.760 6.293 69.914 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -6.600309 4.178311 -1.580 0.115 Yt 0.301254 0.013941 21.609 < 2e-16 *** t -0.048495 0.006567 -7.385 1.08e-12 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 12.43 on 357 degrees of freedom Multiple R-squared: 0.5677, Adjusted R-squared: 0.5653 F-statistic: 234.4 on 2 and 357 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,] 1.838653e-03 3.677306e-03 0.998161347 [2,] 1.672869e-04 3.345739e-04 0.999832713 [3,] 1.963062e-05 3.926123e-05 0.999980369 [4,] 2.692949e-06 5.385899e-06 0.999997307 [5,] 3.417229e-07 6.834458e-07 0.999999658 [6,] 3.654140e-08 7.308280e-08 0.999999963 [7,] 3.862609e-09 7.725219e-09 0.999999996 [8,] 4.418227e-10 8.836454e-10 1.000000000 [9,] 4.106922e-11 8.213843e-11 1.000000000 [10,] 3.706779e-12 7.413558e-12 1.000000000 [11,] 2.841768e-13 5.683535e-13 1.000000000 [12,] 2.075113e-14 4.150226e-14 1.000000000 [13,] 1.435384e-15 2.870768e-15 1.000000000 [14,] 9.599099e-17 1.919820e-16 1.000000000 [15,] 6.712530e-18 1.342506e-17 1.000000000 [16,] 4.247884e-19 8.495767e-19 1.000000000 [17,] 3.933414e-20 7.866828e-20 1.000000000 [18,] 7.129719e-21 1.425944e-20 1.000000000 [19,] 1.994947e-21 3.989893e-21 1.000000000 [20,] 5.937581e-22 1.187516e-21 1.000000000 [21,] 1.071073e-21 2.142146e-21 1.000000000 [22,] 4.384814e-14 8.769628e-14 1.000000000 [23,] 2.530359e-12 5.060717e-12 1.000000000 [24,] 4.044608e-12 8.089216e-12 1.000000000 [25,] 1.062580e-12 2.125160e-12 1.000000000 [26,] 2.487256e-13 4.974512e-13 1.000000000 [27,] 5.954072e-14 1.190814e-13 1.000000000 [28,] 3.044517e-14 6.089034e-14 1.000000000 [29,] 2.194203e-14 4.388406e-14 1.000000000 [30,] 1.908506e-14 3.817012e-14 1.000000000 [31,] 1.625993e-14 3.251987e-14 1.000000000 [32,] 1.685217e-14 3.370435e-14 1.000000000 [33,] 8.067943e-15 1.613589e-14 1.000000000 [34,] 3.492043e-15 6.984086e-15 1.000000000 [35,] 4.810727e-15 9.621454e-15 1.000000000 [36,] 2.936970e-15 5.873940e-15 1.000000000 [37,] 1.208357e-15 2.416714e-15 1.000000000 [38,] 3.719153e-16 7.438306e-16 1.000000000 [39,] 1.055341e-16 2.110682e-16 1.000000000 [40,] 2.961759e-17 5.923518e-17 1.000000000 [41,] 7.833682e-18 1.566736e-17 1.000000000 [42,] 2.060959e-18 4.121917e-18 1.000000000 [43,] 1.277330e-18 2.554660e-18 1.000000000 [44,] 6.745638e-19 1.349128e-18 1.000000000 [45,] 3.829689e-19 7.659377e-19 1.000000000 [46,] 1.783103e-19 3.566206e-19 1.000000000 [47,] 6.793815e-20 1.358763e-19 1.000000000 [48,] 2.232349e-20 4.464698e-20 1.000000000 [49,] 6.215554e-21 1.243111e-20 1.000000000 [50,] 1.659966e-21 3.319932e-21 1.000000000 [51,] 4.406806e-22 8.813612e-22 1.000000000 [52,] 1.227725e-22 2.455451e-22 1.000000000 [53,] 4.464388e-23 8.928777e-23 1.000000000 [54,] 4.062070e-23 8.124139e-23 1.000000000 [55,] 1.798415e-23 3.596830e-23 1.000000000 [56,] 6.045335e-24 1.209067e-23 1.000000000 [57,] 1.566759e-24 3.133517e-24 1.000000000 [58,] 7.073030e-25 1.414606e-24 1.000000000 [59,] 2.969376e-25 5.938752e-25 1.000000000 [60,] 9.293553e-26 1.858711e-25 1.000000000 [61,] 2.531997e-26 5.063994e-26 1.000000000 [62,] 6.665594e-27 1.333119e-26 1.000000000 [63,] 1.788688e-27 3.577377e-27 1.000000000 [64,] 5.217526e-28 1.043505e-27 1.000000000 [65,] 3.937729e-28 7.875458e-28 1.000000000 [66,] 1.582857e-28 3.165714e-28 1.000000000 [67,] 4.563345e-29 9.126691e-29 1.000000000 [68,] 1.229800e-29 2.459600e-29 1.000000000 [69,] 3.713301e-30 7.426602e-30 1.000000000 [70,] 1.512496e-30 3.024993e-30 1.000000000 [71,] 4.219592e-31 8.439184e-31 1.000000000 [72,] 1.203952e-31 2.407905e-31 1.000000000 [73,] 4.185284e-32 8.370568e-32 1.000000000 [74,] 1.977646e-32 3.955292e-32 1.000000000 [75,] 1.605133e-32 3.210266e-32 1.000000000 [76,] 5.131805e-33 1.026361e-32 1.000000000 [77,] 1.520499e-33 3.040999e-33 1.000000000 [78,] 4.701854e-34 9.403708e-34 1.000000000 [79,] 1.867915e-34 3.735830e-34 1.000000000 [80,] 8.317273e-35 1.663455e-34 1.000000000 [81,] 6.763597e-35 1.352719e-34 1.000000000 [82,] 6.737475e-35 1.347495e-34 1.000000000 [83,] 5.786053e-35 1.157211e-34 1.000000000 [84,] 5.042186e-35 1.008437e-34 1.000000000 [85,] 5.467946e-35 1.093589e-34 1.000000000 [86,] 1.174810e-34 2.349621e-34 1.000000000 [87,] 8.680671e-35 1.736134e-34 1.000000000 [88,] 4.617612e-35 9.235225e-35 1.000000000 [89,] 3.747158e-35 7.494317e-35 1.000000000 [90,] 3.395373e-35 6.790747e-35 1.000000000 [91,] 1.935193e-35 3.870386e-35 1.000000000 [92,] 1.655684e-35 3.311368e-35 1.000000000 [93,] 2.698131e-35 5.396262e-35 1.000000000 [94,] 1.810055e-35 3.620109e-35 1.000000000 [95,] 4.258798e-35 8.517597e-35 1.000000000 [96,] 3.489766e-34 6.979531e-34 1.000000000 [97,] 6.452909e-34 1.290582e-33 1.000000000 [98,] 2.447876e-33 4.895751e-33 1.000000000 [99,] 1.356481e-32 2.712962e-32 1.000000000 [100,] 1.952516e-32 3.905032e-32 1.000000000 [101,] 5.042072e-32 1.008414e-31 1.000000000 [102,] 2.933091e-32 5.866182e-32 1.000000000 [103,] 1.479275e-32 2.958550e-32 1.000000000 [104,] 4.536023e-33 9.072046e-33 1.000000000 [105,] 1.187203e-32 2.374406e-32 1.000000000 [106,] 3.667161e-29 7.334322e-29 1.000000000 [107,] 8.691075e-27 1.738215e-26 1.000000000 [108,] 4.692280e-25 9.384559e-25 1.000000000 [109,] 4.708003e-24 9.416005e-24 1.000000000 [110,] 1.693337e-23 3.386675e-23 1.000000000 [111,] 3.955122e-23 7.910244e-23 1.000000000 [112,] 8.262771e-23 1.652554e-22 1.000000000 [113,] 1.118633e-22 2.237265e-22 1.000000000 [114,] 1.553942e-22 3.107883e-22 1.000000000 [115,] 1.332649e-22 2.665298e-22 1.000000000 [116,] 8.801228e-23 1.760246e-22 1.000000000 [117,] 5.314128e-23 1.062826e-22 1.000000000 [118,] 2.838720e-23 5.677439e-23 1.000000000 [119,] 1.477374e-23 2.954749e-23 1.000000000 [120,] 7.662144e-24 1.532429e-23 1.000000000 [121,] 3.538450e-24 7.076900e-24 1.000000000 [122,] 1.533364e-24 3.066728e-24 1.000000000 [123,] 6.919562e-25 1.383912e-24 1.000000000 [124,] 2.843476e-25 5.686951e-25 1.000000000 [125,] 1.171458e-25 2.342916e-25 1.000000000 [126,] 6.905131e-26 1.381026e-25 1.000000000 [127,] 3.831177e-26 7.662354e-26 1.000000000 [128,] 1.763814e-26 3.527629e-26 1.000000000 [129,] 1.007532e-26 2.015065e-26 1.000000000 [130,] 5.350826e-27 1.070165e-26 1.000000000 [131,] 2.655522e-27 5.311043e-27 1.000000000 [132,] 1.273258e-27 2.546515e-27 1.000000000 [133,] 5.486963e-28 1.097393e-27 1.000000000 [134,] 2.181974e-28 4.363949e-28 1.000000000 [135,] 8.920910e-29 1.784182e-28 1.000000000 [136,] 3.940909e-29 7.881818e-29 1.000000000 [137,] 1.595822e-29 3.191644e-29 1.000000000 [138,] 6.828006e-30 1.365601e-29 1.000000000 [139,] 2.627728e-30 5.255455e-30 1.000000000 [140,] 9.903383e-31 1.980677e-30 1.000000000 [141,] 4.776850e-31 9.553700e-31 1.000000000 [142,] 2.470615e-31 4.941229e-31 1.000000000 [143,] 9.085159e-32 1.817032e-31 1.000000000 [144,] 3.416960e-32 6.833920e-32 1.000000000 [145,] 1.240206e-32 2.480411e-32 1.000000000 [146,] 4.780166e-33 9.560331e-33 1.000000000 [147,] 1.905539e-33 3.811078e-33 1.000000000 [148,] 7.776673e-34 1.555335e-33 1.000000000 [149,] 2.994715e-34 5.989430e-34 1.000000000 [150,] 1.083355e-34 2.166711e-34 1.000000000 [151,] 4.045446e-35 8.090891e-35 1.000000000 [152,] 1.681458e-35 3.362915e-35 1.000000000 [153,] 9.662962e-36 1.932592e-35 1.000000000 [154,] 3.705676e-36 7.411353e-36 1.000000000 [155,] 1.312910e-36 2.625819e-36 1.000000000 [156,] 4.926968e-37 9.853936e-37 1.000000000 [157,] 2.291419e-37 4.582837e-37 1.000000000 [158,] 1.679955e-37 3.359910e-37 1.000000000 [159,] 1.523335e-37 3.046670e-37 1.000000000 [160,] 5.262627e-38 1.052525e-37 1.000000000 [161,] 1.881095e-38 3.762190e-38 1.000000000 [162,] 6.750193e-39 1.350039e-38 1.000000000 [163,] 2.709072e-39 5.418143e-39 1.000000000 [164,] 1.269225e-39 2.538450e-39 1.000000000 [165,] 7.550223e-40 1.510045e-39 1.000000000 [166,] 3.019185e-40 6.038371e-40 1.000000000 [167,] 1.000035e-40 2.000069e-40 1.000000000 [168,] 3.320413e-41 6.640825e-41 1.000000000 [169,] 1.123922e-41 2.247845e-41 1.000000000 [170,] 3.866591e-42 7.733182e-42 1.000000000 [171,] 1.360909e-42 2.721819e-42 1.000000000 [172,] 5.108137e-43 1.021627e-42 1.000000000 [173,] 1.766348e-43 3.532695e-43 1.000000000 [174,] 6.214699e-44 1.242940e-43 1.000000000 [175,] 2.276703e-44 4.553406e-44 1.000000000 [176,] 8.252651e-45 1.650530e-44 1.000000000 [177,] 4.733800e-45 9.467601e-45 1.000000000 [178,] 3.310349e-45 6.620698e-45 1.000000000 [179,] 2.403620e-45 4.807240e-45 1.000000000 [180,] 2.216538e-45 4.433076e-45 1.000000000 [181,] 1.997310e-45 3.994620e-45 1.000000000 [182,] 6.333822e-45 1.266764e-44 1.000000000 [183,] 5.351947e-44 1.070389e-43 1.000000000 [184,] 2.708437e-43 5.416874e-43 1.000000000 [185,] 1.045106e-42 2.090212e-42 1.000000000 [186,] 2.415176e-42 4.830351e-42 1.000000000 [187,] 4.985263e-42 9.970525e-42 1.000000000 [188,] 9.675381e-42 1.935076e-41 1.000000000 [189,] 2.967412e-41 5.934825e-41 1.000000000 [190,] 9.342169e-41 1.868434e-40 1.000000000 [191,] 1.221984e-40 2.443968e-40 1.000000000 [192,] 1.544842e-40 3.089683e-40 1.000000000 [193,] 2.328267e-40 4.656535e-40 1.000000000 [194,] 3.919017e-40 7.838035e-40 1.000000000 [195,] 1.631022e-40 3.262044e-40 1.000000000 [196,] 6.921473e-41 1.384295e-40 1.000000000 [197,] 2.772133e-41 5.544266e-41 1.000000000 [198,] 1.131902e-41 2.263804e-41 1.000000000 [199,] 5.206576e-42 1.041315e-41 1.000000000 [200,] 2.748709e-42 5.497417e-42 1.000000000 [201,] 9.873482e-43 1.974696e-42 1.000000000 [202,] 1.992303e-40 3.984605e-40 1.000000000 [203,] 1.889457e-38 3.778914e-38 1.000000000 [204,] 1.111107e-36 2.222214e-36 1.000000000 [205,] 7.435351e-35 1.487070e-34 1.000000000 [206,] 3.715975e-35 7.431950e-35 1.000000000 [207,] 1.823464e-34 3.646929e-34 1.000000000 [208,] 5.218532e-33 1.043706e-32 1.000000000 [209,] 1.197154e-31 2.394308e-31 1.000000000 [210,] 1.164449e-30 2.328898e-30 1.000000000 [211,] 4.348321e-30 8.696641e-30 1.000000000 [212,] 1.172189e-29 2.344377e-29 1.000000000 [213,] 2.539413e-29 5.078825e-29 1.000000000 [214,] 4.266613e-29 8.533226e-29 1.000000000 [215,] 6.176280e-29 1.235256e-28 1.000000000 [216,] 1.267925e-28 2.535850e-28 1.000000000 [217,] 1.564112e-28 3.128223e-28 1.000000000 [218,] 1.613113e-28 3.226226e-28 1.000000000 [219,] 1.579244e-28 3.158487e-28 1.000000000 [220,] 1.445028e-28 2.890056e-28 1.000000000 [221,] 1.061327e-28 2.122653e-28 1.000000000 [222,] 7.333611e-29 1.466722e-28 1.000000000 [223,] 4.867541e-29 9.735081e-29 1.000000000 [224,] 2.500161e-29 5.000323e-29 1.000000000 [225,] 1.416259e-29 2.832518e-29 1.000000000 [226,] 8.005797e-30 1.601159e-29 1.000000000 [227,] 3.970628e-30 7.941256e-30 1.000000000 [228,] 2.173539e-30 4.347079e-30 1.000000000 [229,] 1.094748e-30 2.189496e-30 1.000000000 [230,] 8.291669e-31 1.658334e-30 1.000000000 [231,] 4.195336e-29 8.390671e-29 1.000000000 [232,] 6.631238e-27 1.326248e-26 1.000000000 [233,] 1.734453e-24 3.468905e-24 1.000000000 [234,] 6.884422e-22 1.376884e-21 1.000000000 [235,] 1.011386e-20 2.022773e-20 1.000000000 [236,] 4.503147e-20 9.006295e-20 1.000000000 [237,] 9.117263e-17 1.823453e-16 1.000000000 [238,] 1.163677e-06 2.327354e-06 0.999998836 [239,] 5.163052e-04 1.032610e-03 0.999483695 [240,] 2.077717e-01 4.155435e-01 0.792228269 [241,] 7.422019e-01 5.155963e-01 0.257798146 [242,] 7.328364e-01 5.343272e-01 0.267163585 [243,] 7.505032e-01 4.989936e-01 0.249496787 [244,] 7.924082e-01 4.151836e-01 0.207591824 [245,] 8.060294e-01 3.879412e-01 0.193970592 [246,] 8.264529e-01 3.470943e-01 0.173547128 [247,] 8.113087e-01 3.773825e-01 0.188691264 [248,] 8.024701e-01 3.950598e-01 0.197529907 [249,] 8.390427e-01 3.219147e-01 0.160957326 [250,] 8.195037e-01 3.609927e-01 0.180496344 [251,] 8.026409e-01 3.947181e-01 0.197359066 [252,] 7.793233e-01 4.413534e-01 0.220676675 [253,] 7.537226e-01 4.925547e-01 0.246277362 [254,] 7.281600e-01 5.436800e-01 0.271839989 [255,] 7.064308e-01 5.871383e-01 0.293569167 [256,] 6.789008e-01 6.421984e-01 0.321099202 [257,] 6.621243e-01 6.757513e-01 0.337875658 [258,] 6.782119e-01 6.435763e-01 0.321788145 [259,] 7.203886e-01 5.592229e-01 0.279611442 [260,] 7.610885e-01 4.778230e-01 0.238911524 [261,] 7.873578e-01 4.252845e-01 0.212642241 [262,] 8.066682e-01 3.866637e-01 0.193331832 [263,] 8.236462e-01 3.527076e-01 0.176353817 [264,] 8.279139e-01 3.441722e-01 0.172086091 [265,] 8.543425e-01 2.913149e-01 0.145657457 [266,] 8.574577e-01 2.850846e-01 0.142542310 [267,] 8.532165e-01 2.935669e-01 0.146783459 [268,] 8.454740e-01 3.090521e-01 0.154526029 [269,] 8.313100e-01 3.373800e-01 0.168689988 [270,] 8.684137e-01 2.631727e-01 0.131586348 [271,] 9.617525e-01 7.649492e-02 0.038247461 [272,] 9.660250e-01 6.794992e-02 0.033974961 [273,] 9.604922e-01 7.901552e-02 0.039507760 [274,] 9.553741e-01 8.925176e-02 0.044625880 [275,] 9.494134e-01 1.011732e-01 0.050586610 [276,] 9.440039e-01 1.119923e-01 0.055996139 [277,] 9.388878e-01 1.222243e-01 0.061112169 [278,] 9.326922e-01 1.346157e-01 0.067307843 [279,] 9.260485e-01 1.479030e-01 0.073951504 [280,] 9.194728e-01 1.610544e-01 0.080527207 [281,] 9.142532e-01 1.714936e-01 0.085746799 [282,] 9.185343e-01 1.629315e-01 0.081465739 [283,] 9.244655e-01 1.510691e-01 0.075534532 [284,] 9.242516e-01 1.514968e-01 0.075748398 [285,] 9.190092e-01 1.619816e-01 0.080990822 [286,] 9.131919e-01 1.736163e-01 0.086808148 [287,] 9.151749e-01 1.696503e-01 0.084825140 [288,] 9.328756e-01 1.342488e-01 0.067124394 [289,] 9.282625e-01 1.434750e-01 0.071737523 [290,] 9.239493e-01 1.521014e-01 0.076050694 [291,] 9.217869e-01 1.564263e-01 0.078213137 [292,] 9.223796e-01 1.552409e-01 0.077620435 [293,] 9.162771e-01 1.674459e-01 0.083722944 [294,] 9.130356e-01 1.739289e-01 0.086964445 [295,] 9.117183e-01 1.765633e-01 0.088281671 [296,] 9.136948e-01 1.726104e-01 0.086305179 [297,] 9.118915e-01 1.762169e-01 0.088108462 [298,] 9.329843e-01 1.340314e-01 0.067015720 [299,] 9.529776e-01 9.404487e-02 0.047022437 [300,] 9.559102e-01 8.817962e-02 0.044089809 [301,] 9.573036e-01 8.539289e-02 0.042696443 [302,] 9.515014e-01 9.699717e-02 0.048498583 [303,] 9.442362e-01 1.115277e-01 0.055763843 [304,] 9.375449e-01 1.249103e-01 0.062455146 [305,] 9.303523e-01 1.392954e-01 0.069647716 [306,] 9.276603e-01 1.446794e-01 0.072339682 [307,] 9.148574e-01 1.702852e-01 0.085142583 [308,] 9.009745e-01 1.980511e-01 0.099025545 [309,] 8.837729e-01 2.324542e-01 0.116227115 [310,] 8.654086e-01 2.691828e-01 0.134591401 [311,] 8.442735e-01 3.114530e-01 0.155726479 [312,] 8.172408e-01 3.655184e-01 0.182759215 [313,] 7.946245e-01 4.107509e-01 0.205375464 [314,] 7.626313e-01 4.747373e-01 0.237368673 [315,] 7.387615e-01 5.224771e-01 0.261238534 [316,] 7.174589e-01 5.650822e-01 0.282541110 [317,] 6.987594e-01 6.024811e-01 0.301240573 [318,] 6.776704e-01 6.446591e-01 0.322329550 [319,] 6.712517e-01 6.574967e-01 0.328748327 [320,] 6.364788e-01 7.270424e-01 0.363521224 [321,] 6.022619e-01 7.954763e-01 0.397738136 [322,] 5.704964e-01 8.590071e-01 0.429503573 [323,] 5.618139e-01 8.763721e-01 0.438186072 [324,] 5.433512e-01 9.132976e-01 0.456648822 [325,] 4.968029e-01 9.936057e-01 0.503197147 [326,] 5.627409e-01 8.745182e-01 0.437259090 [327,] 6.704827e-01 6.590346e-01 0.329517315 [328,] 7.297454e-01 5.405092e-01 0.270254609 [329,] 8.557749e-01 2.884502e-01 0.144225113 [330,] 9.264776e-01 1.470448e-01 0.073522387 [331,] 9.641872e-01 7.162562e-02 0.035812811 [332,] 9.876326e-01 2.473477e-02 0.012367385 [333,] 9.939638e-01 1.207234e-02 0.006036172 [334,] 9.919300e-01 1.614010e-02 0.008070048 [335,] 9.886291e-01 2.274182e-02 0.011370910 [336,] 9.870538e-01 2.589240e-02 0.012946199 [337,] 9.821460e-01 3.570805e-02 0.017854024 [338,] 9.769093e-01 4.618137e-02 0.023090684 [339,] 9.622647e-01 7.547068e-02 0.037735342 [340,] 9.637303e-01 7.253940e-02 0.036269702 [341,] 9.418535e-01 1.162929e-01 0.058146455 [342,] 9.091085e-01 1.817830e-01 0.090891513 [343,] 8.658930e-01 2.682141e-01 0.134107040 [344,] 9.292434e-01 1.415133e-01 0.070756632 [345,] 9.713552e-01 5.728960e-02 0.028644799 [346,] 9.604945e-01 7.901107e-02 0.039505534 [347,] 9.673039e-01 6.539215e-02 0.032696077 [348,] 9.333311e-01 1.333378e-01 0.066668880 [349,] 8.554415e-01 2.891169e-01 0.144558467 > postscript(file="/var/wessaorg/rcomp/tmp/1e3021321473905.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2yfjg1321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3xh581321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4whj01321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5pyfh1321473905.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 = 360 Frequency = 1 1 2 3 4 5 1.710906e+01 9.565960e+00 3.489754e+00 -8.471028e+00 -1.829642e+01 6 7 8 9 10 -2.093212e+01 -1.961824e+01 -1.770034e+01 -1.644369e+01 -1.513742e+01 11 12 13 14 15 -1.212438e+01 -1.106924e+01 -1.008372e+01 -9.200714e+00 -8.788959e+00 16 17 18 19 20 -5.505417e+00 -4.190150e+00 -1.890872e+00 -5.356053e-01 3.671573e+00 21 22 23 24 25 5.520601e+00 5.784613e+00 5.224237e+00 4.964613e+00 5.598501e+00 26 27 28 29 30 5.262137e+00 -1.970591e+00 -1.567707e+00 3.431711e-01 2.865773e+00 31 32 33 34 35 -1.863317e+00 -7.838175e+00 -7.263222e+00 -7.190870e+00 -7.167767e+00 36 37 38 39 40 -6.961779e+00 -3.178363e+00 -5.806889e+00 -4.279616e+00 1.755246e-01 41 42 43 44 45 -1.518488e+00 -1.977109e+00 -4.747265e+00 -4.644883e+00 -2.182594e+00 46 47 48 49 50 -1.466701e+00 1.609098e+00 7.399881e+00 8.002514e+00 1.176057e+01 51 52 53 54 55 1.264596e+01 1.266734e+01 1.271910e+01 1.147621e+01 1.159897e+01 56 57 58 59 60 1.111947e+01 1.045910e+01 1.417709e+01 1.761960e+01 1.416681e+01 61 62 63 64 65 1.359756e+01 9.241762e+00 1.231888e+01 1.221700e+01 1.106487e+01 66 67 68 69 70 1.053562e+01 1.055775e+01 9.104615e+00 8.644866e+00 1.534625e+01 71 72 73 74 75 1.400587e+01 1.230374e+01 1.059010e+01 8.896591e+00 7.424835e+00 76 77 78 79 80 1.039847e+01 1.021747e+01 9.116967e+00 8.197092e+00 6.293707e+00 81 82 83 84 85 9.604961e+00 9.872202e+00 8.827688e+00 8.078942e+00 6.471920e+00 86 87 88 89 90 3.433519e+00 3.204773e+00 2.922015e+00 2.238880e+00 5.829868e-01 91 92 93 94 95 -1.681527e+00 6.784589e-02 2.647112e-01 -1.377922e+00 -1.758047e+00 96 97 98 99 100 -1.240806e+00 -2.632310e+00 -4.926323e+00 -3.568329e+00 -6.468831e+00 101 102 103 104 105 -8.969332e+00 -7.391464e+00 -9.453345e+00 -9.518329e+00 -7.288329e+00 106 107 108 109 110 -9.441213e+00 -5.781338e+00 -3.403063e+00 -3.880021e+00 -1.948673e+01 111 112 113 114 115 -1.090381e+01 -7.396789e+00 -5.173404e+00 -5.200896e+00 -4.553247e+00 116 117 118 119 120 -1.987824e+00 2.165247e+00 1.545874e+00 1.559856e+00 -8.966338e-04 121 122 123 124 125 -6.085142e-01 3.998868e-01 6.054040e-01 2.035686e+00 3.586469e+00 126 127 128 129 130 2.736595e+00 2.378852e+00 4.189510e+00 2.023115e+00 1.633585e+00 131 132 133 134 135 6.947127e+00 6.939510e+00 4.065341e+00 5.943460e+00 6.250106e+00 136 137 138 139 140 4.798946e+00 4.729699e+00 3.570075e+00 2.707960e-01 1.746831e-01 141 142 143 144 145 -1.527950e+00 -5.613355e-01 2.702520e+00 3.268780e-01 -7.295168e-01 146 147 148 149 150 -6.362056e+00 -6.811930e+00 -2.592964e+00 -5.680488e+00 -4.932494e+00 151 152 153 154 155 -7.161271e+00 -6.986005e+00 -6.288356e+00 -4.802337e+00 -1.769145e-01 156 157 158 159 160 -2.782682e+00 -3.881679e+00 -7.079203e+00 -2.821428e+00 -3.921808e-01 161 162 163 164 165 -3.630331e+00 -6.366726e+00 -1.012789e+01 -1.076600e+01 -4.367258e+00 166 167 168 169 170 -5.289390e+00 -4.090237e+00 -5.411240e+00 -6.763246e+00 -8.648011e+00 171 172 173 174 175 -5.039860e+00 -2.235127e+00 -1.990989e+00 -2.710863e+00 -1.934719e+00 176 177 178 179 180 -6.160675e-01 -1.103560e+00 2.931802e-01 7.258134e-01 9.503274e-01 181 182 183 184 185 -2.965689e-01 -4.610581e+00 -4.704939e+00 -4.744061e+00 -6.791584e+00 186 187 188 189 190 -6.348700e+00 -1.091359e+01 -1.304021e+01 -1.126218e+01 -1.041804e+01 191 192 193 194 195 -7.866883e+00 -7.565002e+00 -7.655002e+00 -1.109905e+01 -1.182180e+01 196 197 198 199 200 -9.615189e+00 -1.035133e+01 -1.157522e+01 -1.247861e+01 -4.674092e+00 201 202 203 204 205 -4.964719e+00 -3.116443e+00 -3.890205e+00 -6.047603e+00 -7.975377e+00 206 207 208 209 210 -1.046756e+00 1.907349e+01 1.792186e+01 1.655798e+01 1.566857e+01 211 212 213 214 215 -7.946095e+00 -2.261042e+01 -7.699163e+00 -4.799665e+00 -5.985182e+00 216 217 218 219 220 -7.004148e+00 -9.407659e+00 -5.318599e+00 -3.554305e+00 -3.562800e+00 221 222 223 224 225 2.782651e-02 -3.062675e+00 -4.010167e+00 -8.344681e+00 -8.109289e+00 226 227 228 229 230 -7.364368e+00 -5.659478e+00 -3.833209e+00 -4.822770e+00 -2.565905e+00 231 232 233 234 235 -1.762394e+00 -3.961015e+00 -6.621120e-01 -1.592864e+00 2.902904e+00 236 237 238 239 240 1.844015e+01 2.213579e+01 2.438290e+01 2.630905e+01 1.787453e+01 241 242 243 244 245 1.332391e+01 3.188040e+01 6.991432e+01 4.850491e+01 6.658645e+01 246 247 248 249 250 5.708495e+01 1.186836e+01 3.991717e+00 7.667327e-01 1.863441e+00 251 252 253 254 255 -3.769045e-01 1.131940e+01 1.524494e+01 2.387996e+01 7.060932e+00 256 257 258 259 260 1.101871e+01 2.017358e+00 3.267389e+00 4.757765e+00 5.594662e+00 261 262 263 264 265 -2.463105e-01 1.686855e+00 7.797984e+00 1.001099e+01 9.170868e+00 266 267 268 269 270 6.520241e+00 6.292718e+00 5.162467e+00 2.707326e+00 5.045100e+00 271 272 273 274 275 -8.462792e-01 -3.588787e+00 -6.685903e+00 -9.348567e+00 3.908110e+00 276 277 278 279 280 1.588535e+01 8.696463e-01 -8.299037e+00 -5.835024e+00 -8.480385e+00 281 282 283 284 285 -7.985244e+00 -1.031421e+01 -1.103759e+01 -1.491885e+01 -1.254719e+01 286 287 288 289 290 -1.069593e+01 -7.108160e+00 -7.645777e+00 -1.120879e+01 -1.728941e+01 291 292 293 294 295 -1.666941e+01 -1.110126e+01 -6.208881e+00 -1.859778e+01 -1.716189e+01 296 297 298 299 300 -1.495700e+01 -1.337587e+01 -1.888612e+01 -1.503424e+01 -1.365634e+01 301 302 303 304 305 -1.217073e+01 -1.389349e+01 -6.054085e+00 -6.460260e+00 -1.340615e+01 306 307 308 309 310 -1.374850e+01 -2.178490e+01 -2.213039e+01 -1.641089e+01 -1.488625e+01 311 312 313 314 315 -1.177901e+01 -1.753499e+01 -1.811669e+01 -1.718879e+01 -2.063142e+01 316 317 318 319 320 -2.024233e+01 -1.654493e+01 -1.974568e+01 -1.610882e+01 -1.829744e+01 321 322 323 324 325 -1.771869e+01 -1.604841e+01 -1.378415e+01 -1.513769e+01 -9.221325e+00 326 327 328 329 330 -7.808315e+00 -7.649349e+00 -8.907845e+00 -4.959695e+00 2.948957e+00 331 332 333 334 335 -9.288597e+00 -8.260102e+00 -1.291105e+00 -1.368346e+00 8.757923e+00 336 337 338 339 340 1.849667e+01 1.109093e+01 2.810310e+01 4.002294e+01 2.566247e+01 341 342 343 344 345 2.014981e+01 1.072739e+01 3.436170e+00 -1.033892e+00 -4.691008e+00 346 347 348 349 350 5.127487e+00 1.357529e+01 1.544106e+01 3.088993e+01 2.327570e+01 351 352 353 354 355 1.344827e+01 1.493789e+01 9.799243e+00 8.611687e+00 1.002068e+01 356 357 358 359 360 1.493391e+01 1.196529e+01 1.164818e+01 2.327416e+01 3.245830e+01 > postscript(file="/var/wessaorg/rcomp/tmp/681p81321473905.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 = 360 Frequency = 1 lag(myerror, k = 1) myerror 0 1.710906e+01 NA 1 9.565960e+00 1.710906e+01 2 3.489754e+00 9.565960e+00 3 -8.471028e+00 3.489754e+00 4 -1.829642e+01 -8.471028e+00 5 -2.093212e+01 -1.829642e+01 6 -1.961824e+01 -2.093212e+01 7 -1.770034e+01 -1.961824e+01 8 -1.644369e+01 -1.770034e+01 9 -1.513742e+01 -1.644369e+01 10 -1.212438e+01 -1.513742e+01 11 -1.106924e+01 -1.212438e+01 12 -1.008372e+01 -1.106924e+01 13 -9.200714e+00 -1.008372e+01 14 -8.788959e+00 -9.200714e+00 15 -5.505417e+00 -8.788959e+00 16 -4.190150e+00 -5.505417e+00 17 -1.890872e+00 -4.190150e+00 18 -5.356053e-01 -1.890872e+00 19 3.671573e+00 -5.356053e-01 20 5.520601e+00 3.671573e+00 21 5.784613e+00 5.520601e+00 22 5.224237e+00 5.784613e+00 23 4.964613e+00 5.224237e+00 24 5.598501e+00 4.964613e+00 25 5.262137e+00 5.598501e+00 26 -1.970591e+00 5.262137e+00 27 -1.567707e+00 -1.970591e+00 28 3.431711e-01 -1.567707e+00 29 2.865773e+00 3.431711e-01 30 -1.863317e+00 2.865773e+00 31 -7.838175e+00 -1.863317e+00 32 -7.263222e+00 -7.838175e+00 33 -7.190870e+00 -7.263222e+00 34 -7.167767e+00 -7.190870e+00 35 -6.961779e+00 -7.167767e+00 36 -3.178363e+00 -6.961779e+00 37 -5.806889e+00 -3.178363e+00 38 -4.279616e+00 -5.806889e+00 39 1.755246e-01 -4.279616e+00 40 -1.518488e+00 1.755246e-01 41 -1.977109e+00 -1.518488e+00 42 -4.747265e+00 -1.977109e+00 43 -4.644883e+00 -4.747265e+00 44 -2.182594e+00 -4.644883e+00 45 -1.466701e+00 -2.182594e+00 46 1.609098e+00 -1.466701e+00 47 7.399881e+00 1.609098e+00 48 8.002514e+00 7.399881e+00 49 1.176057e+01 8.002514e+00 50 1.264596e+01 1.176057e+01 51 1.266734e+01 1.264596e+01 52 1.271910e+01 1.266734e+01 53 1.147621e+01 1.271910e+01 54 1.159897e+01 1.147621e+01 55 1.111947e+01 1.159897e+01 56 1.045910e+01 1.111947e+01 57 1.417709e+01 1.045910e+01 58 1.761960e+01 1.417709e+01 59 1.416681e+01 1.761960e+01 60 1.359756e+01 1.416681e+01 61 9.241762e+00 1.359756e+01 62 1.231888e+01 9.241762e+00 63 1.221700e+01 1.231888e+01 64 1.106487e+01 1.221700e+01 65 1.053562e+01 1.106487e+01 66 1.055775e+01 1.053562e+01 67 9.104615e+00 1.055775e+01 68 8.644866e+00 9.104615e+00 69 1.534625e+01 8.644866e+00 70 1.400587e+01 1.534625e+01 71 1.230374e+01 1.400587e+01 72 1.059010e+01 1.230374e+01 73 8.896591e+00 1.059010e+01 74 7.424835e+00 8.896591e+00 75 1.039847e+01 7.424835e+00 76 1.021747e+01 1.039847e+01 77 9.116967e+00 1.021747e+01 78 8.197092e+00 9.116967e+00 79 6.293707e+00 8.197092e+00 80 9.604961e+00 6.293707e+00 81 9.872202e+00 9.604961e+00 82 8.827688e+00 9.872202e+00 83 8.078942e+00 8.827688e+00 84 6.471920e+00 8.078942e+00 85 3.433519e+00 6.471920e+00 86 3.204773e+00 3.433519e+00 87 2.922015e+00 3.204773e+00 88 2.238880e+00 2.922015e+00 89 5.829868e-01 2.238880e+00 90 -1.681527e+00 5.829868e-01 91 6.784589e-02 -1.681527e+00 92 2.647112e-01 6.784589e-02 93 -1.377922e+00 2.647112e-01 94 -1.758047e+00 -1.377922e+00 95 -1.240806e+00 -1.758047e+00 96 -2.632310e+00 -1.240806e+00 97 -4.926323e+00 -2.632310e+00 98 -3.568329e+00 -4.926323e+00 99 -6.468831e+00 -3.568329e+00 100 -8.969332e+00 -6.468831e+00 101 -7.391464e+00 -8.969332e+00 102 -9.453345e+00 -7.391464e+00 103 -9.518329e+00 -9.453345e+00 104 -7.288329e+00 -9.518329e+00 105 -9.441213e+00 -7.288329e+00 106 -5.781338e+00 -9.441213e+00 107 -3.403063e+00 -5.781338e+00 108 -3.880021e+00 -3.403063e+00 109 -1.948673e+01 -3.880021e+00 110 -1.090381e+01 -1.948673e+01 111 -7.396789e+00 -1.090381e+01 112 -5.173404e+00 -7.396789e+00 113 -5.200896e+00 -5.173404e+00 114 -4.553247e+00 -5.200896e+00 115 -1.987824e+00 -4.553247e+00 116 2.165247e+00 -1.987824e+00 117 1.545874e+00 2.165247e+00 118 1.559856e+00 1.545874e+00 119 -8.966338e-04 1.559856e+00 120 -6.085142e-01 -8.966338e-04 121 3.998868e-01 -6.085142e-01 122 6.054040e-01 3.998868e-01 123 2.035686e+00 6.054040e-01 124 3.586469e+00 2.035686e+00 125 2.736595e+00 3.586469e+00 126 2.378852e+00 2.736595e+00 127 4.189510e+00 2.378852e+00 128 2.023115e+00 4.189510e+00 129 1.633585e+00 2.023115e+00 130 6.947127e+00 1.633585e+00 131 6.939510e+00 6.947127e+00 132 4.065341e+00 6.939510e+00 133 5.943460e+00 4.065341e+00 134 6.250106e+00 5.943460e+00 135 4.798946e+00 6.250106e+00 136 4.729699e+00 4.798946e+00 137 3.570075e+00 4.729699e+00 138 2.707960e-01 3.570075e+00 139 1.746831e-01 2.707960e-01 140 -1.527950e+00 1.746831e-01 141 -5.613355e-01 -1.527950e+00 142 2.702520e+00 -5.613355e-01 143 3.268780e-01 2.702520e+00 144 -7.295168e-01 3.268780e-01 145 -6.362056e+00 -7.295168e-01 146 -6.811930e+00 -6.362056e+00 147 -2.592964e+00 -6.811930e+00 148 -5.680488e+00 -2.592964e+00 149 -4.932494e+00 -5.680488e+00 150 -7.161271e+00 -4.932494e+00 151 -6.986005e+00 -7.161271e+00 152 -6.288356e+00 -6.986005e+00 153 -4.802337e+00 -6.288356e+00 154 -1.769145e-01 -4.802337e+00 155 -2.782682e+00 -1.769145e-01 156 -3.881679e+00 -2.782682e+00 157 -7.079203e+00 -3.881679e+00 158 -2.821428e+00 -7.079203e+00 159 -3.921808e-01 -2.821428e+00 160 -3.630331e+00 -3.921808e-01 161 -6.366726e+00 -3.630331e+00 162 -1.012789e+01 -6.366726e+00 163 -1.076600e+01 -1.012789e+01 164 -4.367258e+00 -1.076600e+01 165 -5.289390e+00 -4.367258e+00 166 -4.090237e+00 -5.289390e+00 167 -5.411240e+00 -4.090237e+00 168 -6.763246e+00 -5.411240e+00 169 -8.648011e+00 -6.763246e+00 170 -5.039860e+00 -8.648011e+00 171 -2.235127e+00 -5.039860e+00 172 -1.990989e+00 -2.235127e+00 173 -2.710863e+00 -1.990989e+00 174 -1.934719e+00 -2.710863e+00 175 -6.160675e-01 -1.934719e+00 176 -1.103560e+00 -6.160675e-01 177 2.931802e-01 -1.103560e+00 178 7.258134e-01 2.931802e-01 179 9.503274e-01 7.258134e-01 180 -2.965689e-01 9.503274e-01 181 -4.610581e+00 -2.965689e-01 182 -4.704939e+00 -4.610581e+00 183 -4.744061e+00 -4.704939e+00 184 -6.791584e+00 -4.744061e+00 185 -6.348700e+00 -6.791584e+00 186 -1.091359e+01 -6.348700e+00 187 -1.304021e+01 -1.091359e+01 188 -1.126218e+01 -1.304021e+01 189 -1.041804e+01 -1.126218e+01 190 -7.866883e+00 -1.041804e+01 191 -7.565002e+00 -7.866883e+00 192 -7.655002e+00 -7.565002e+00 193 -1.109905e+01 -7.655002e+00 194 -1.182180e+01 -1.109905e+01 195 -9.615189e+00 -1.182180e+01 196 -1.035133e+01 -9.615189e+00 197 -1.157522e+01 -1.035133e+01 198 -1.247861e+01 -1.157522e+01 199 -4.674092e+00 -1.247861e+01 200 -4.964719e+00 -4.674092e+00 201 -3.116443e+00 -4.964719e+00 202 -3.890205e+00 -3.116443e+00 203 -6.047603e+00 -3.890205e+00 204 -7.975377e+00 -6.047603e+00 205 -1.046756e+00 -7.975377e+00 206 1.907349e+01 -1.046756e+00 207 1.792186e+01 1.907349e+01 208 1.655798e+01 1.792186e+01 209 1.566857e+01 1.655798e+01 210 -7.946095e+00 1.566857e+01 211 -2.261042e+01 -7.946095e+00 212 -7.699163e+00 -2.261042e+01 213 -4.799665e+00 -7.699163e+00 214 -5.985182e+00 -4.799665e+00 215 -7.004148e+00 -5.985182e+00 216 -9.407659e+00 -7.004148e+00 217 -5.318599e+00 -9.407659e+00 218 -3.554305e+00 -5.318599e+00 219 -3.562800e+00 -3.554305e+00 220 2.782651e-02 -3.562800e+00 221 -3.062675e+00 2.782651e-02 222 -4.010167e+00 -3.062675e+00 223 -8.344681e+00 -4.010167e+00 224 -8.109289e+00 -8.344681e+00 225 -7.364368e+00 -8.109289e+00 226 -5.659478e+00 -7.364368e+00 227 -3.833209e+00 -5.659478e+00 228 -4.822770e+00 -3.833209e+00 229 -2.565905e+00 -4.822770e+00 230 -1.762394e+00 -2.565905e+00 231 -3.961015e+00 -1.762394e+00 232 -6.621120e-01 -3.961015e+00 233 -1.592864e+00 -6.621120e-01 234 2.902904e+00 -1.592864e+00 235 1.844015e+01 2.902904e+00 236 2.213579e+01 1.844015e+01 237 2.438290e+01 2.213579e+01 238 2.630905e+01 2.438290e+01 239 1.787453e+01 2.630905e+01 240 1.332391e+01 1.787453e+01 241 3.188040e+01 1.332391e+01 242 6.991432e+01 3.188040e+01 243 4.850491e+01 6.991432e+01 244 6.658645e+01 4.850491e+01 245 5.708495e+01 6.658645e+01 246 1.186836e+01 5.708495e+01 247 3.991717e+00 1.186836e+01 248 7.667327e-01 3.991717e+00 249 1.863441e+00 7.667327e-01 250 -3.769045e-01 1.863441e+00 251 1.131940e+01 -3.769045e-01 252 1.524494e+01 1.131940e+01 253 2.387996e+01 1.524494e+01 254 7.060932e+00 2.387996e+01 255 1.101871e+01 7.060932e+00 256 2.017358e+00 1.101871e+01 257 3.267389e+00 2.017358e+00 258 4.757765e+00 3.267389e+00 259 5.594662e+00 4.757765e+00 260 -2.463105e-01 5.594662e+00 261 1.686855e+00 -2.463105e-01 262 7.797984e+00 1.686855e+00 263 1.001099e+01 7.797984e+00 264 9.170868e+00 1.001099e+01 265 6.520241e+00 9.170868e+00 266 6.292718e+00 6.520241e+00 267 5.162467e+00 6.292718e+00 268 2.707326e+00 5.162467e+00 269 5.045100e+00 2.707326e+00 270 -8.462792e-01 5.045100e+00 271 -3.588787e+00 -8.462792e-01 272 -6.685903e+00 -3.588787e+00 273 -9.348567e+00 -6.685903e+00 274 3.908110e+00 -9.348567e+00 275 1.588535e+01 3.908110e+00 276 8.696463e-01 1.588535e+01 277 -8.299037e+00 8.696463e-01 278 -5.835024e+00 -8.299037e+00 279 -8.480385e+00 -5.835024e+00 280 -7.985244e+00 -8.480385e+00 281 -1.031421e+01 -7.985244e+00 282 -1.103759e+01 -1.031421e+01 283 -1.491885e+01 -1.103759e+01 284 -1.254719e+01 -1.491885e+01 285 -1.069593e+01 -1.254719e+01 286 -7.108160e+00 -1.069593e+01 287 -7.645777e+00 -7.108160e+00 288 -1.120879e+01 -7.645777e+00 289 -1.728941e+01 -1.120879e+01 290 -1.666941e+01 -1.728941e+01 291 -1.110126e+01 -1.666941e+01 292 -6.208881e+00 -1.110126e+01 293 -1.859778e+01 -6.208881e+00 294 -1.716189e+01 -1.859778e+01 295 -1.495700e+01 -1.716189e+01 296 -1.337587e+01 -1.495700e+01 297 -1.888612e+01 -1.337587e+01 298 -1.503424e+01 -1.888612e+01 299 -1.365634e+01 -1.503424e+01 300 -1.217073e+01 -1.365634e+01 301 -1.389349e+01 -1.217073e+01 302 -6.054085e+00 -1.389349e+01 303 -6.460260e+00 -6.054085e+00 304 -1.340615e+01 -6.460260e+00 305 -1.374850e+01 -1.340615e+01 306 -2.178490e+01 -1.374850e+01 307 -2.213039e+01 -2.178490e+01 308 -1.641089e+01 -2.213039e+01 309 -1.488625e+01 -1.641089e+01 310 -1.177901e+01 -1.488625e+01 311 -1.753499e+01 -1.177901e+01 312 -1.811669e+01 -1.753499e+01 313 -1.718879e+01 -1.811669e+01 314 -2.063142e+01 -1.718879e+01 315 -2.024233e+01 -2.063142e+01 316 -1.654493e+01 -2.024233e+01 317 -1.974568e+01 -1.654493e+01 318 -1.610882e+01 -1.974568e+01 319 -1.829744e+01 -1.610882e+01 320 -1.771869e+01 -1.829744e+01 321 -1.604841e+01 -1.771869e+01 322 -1.378415e+01 -1.604841e+01 323 -1.513769e+01 -1.378415e+01 324 -9.221325e+00 -1.513769e+01 325 -7.808315e+00 -9.221325e+00 326 -7.649349e+00 -7.808315e+00 327 -8.907845e+00 -7.649349e+00 328 -4.959695e+00 -8.907845e+00 329 2.948957e+00 -4.959695e+00 330 -9.288597e+00 2.948957e+00 331 -8.260102e+00 -9.288597e+00 332 -1.291105e+00 -8.260102e+00 333 -1.368346e+00 -1.291105e+00 334 8.757923e+00 -1.368346e+00 335 1.849667e+01 8.757923e+00 336 1.109093e+01 1.849667e+01 337 2.810310e+01 1.109093e+01 338 4.002294e+01 2.810310e+01 339 2.566247e+01 4.002294e+01 340 2.014981e+01 2.566247e+01 341 1.072739e+01 2.014981e+01 342 3.436170e+00 1.072739e+01 343 -1.033892e+00 3.436170e+00 344 -4.691008e+00 -1.033892e+00 345 5.127487e+00 -4.691008e+00 346 1.357529e+01 5.127487e+00 347 1.544106e+01 1.357529e+01 348 3.088993e+01 1.544106e+01 349 2.327570e+01 3.088993e+01 350 1.344827e+01 2.327570e+01 351 1.493789e+01 1.344827e+01 352 9.799243e+00 1.493789e+01 353 8.611687e+00 9.799243e+00 354 1.002068e+01 8.611687e+00 355 1.493391e+01 1.002068e+01 356 1.196529e+01 1.493391e+01 357 1.164818e+01 1.196529e+01 358 2.327416e+01 1.164818e+01 359 3.245830e+01 2.327416e+01 360 NA 3.245830e+01 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 9.565960e+00 1.710906e+01 [2,] 3.489754e+00 9.565960e+00 [3,] -8.471028e+00 3.489754e+00 [4,] -1.829642e+01 -8.471028e+00 [5,] -2.093212e+01 -1.829642e+01 [6,] -1.961824e+01 -2.093212e+01 [7,] -1.770034e+01 -1.961824e+01 [8,] -1.644369e+01 -1.770034e+01 [9,] -1.513742e+01 -1.644369e+01 [10,] -1.212438e+01 -1.513742e+01 [11,] -1.106924e+01 -1.212438e+01 [12,] -1.008372e+01 -1.106924e+01 [13,] -9.200714e+00 -1.008372e+01 [14,] -8.788959e+00 -9.200714e+00 [15,] -5.505417e+00 -8.788959e+00 [16,] -4.190150e+00 -5.505417e+00 [17,] -1.890872e+00 -4.190150e+00 [18,] -5.356053e-01 -1.890872e+00 [19,] 3.671573e+00 -5.356053e-01 [20,] 5.520601e+00 3.671573e+00 [21,] 5.784613e+00 5.520601e+00 [22,] 5.224237e+00 5.784613e+00 [23,] 4.964613e+00 5.224237e+00 [24,] 5.598501e+00 4.964613e+00 [25,] 5.262137e+00 5.598501e+00 [26,] -1.970591e+00 5.262137e+00 [27,] -1.567707e+00 -1.970591e+00 [28,] 3.431711e-01 -1.567707e+00 [29,] 2.865773e+00 3.431711e-01 [30,] -1.863317e+00 2.865773e+00 [31,] -7.838175e+00 -1.863317e+00 [32,] -7.263222e+00 -7.838175e+00 [33,] -7.190870e+00 -7.263222e+00 [34,] -7.167767e+00 -7.190870e+00 [35,] -6.961779e+00 -7.167767e+00 [36,] -3.178363e+00 -6.961779e+00 [37,] -5.806889e+00 -3.178363e+00 [38,] -4.279616e+00 -5.806889e+00 [39,] 1.755246e-01 -4.279616e+00 [40,] -1.518488e+00 1.755246e-01 [41,] -1.977109e+00 -1.518488e+00 [42,] -4.747265e+00 -1.977109e+00 [43,] -4.644883e+00 -4.747265e+00 [44,] -2.182594e+00 -4.644883e+00 [45,] -1.466701e+00 -2.182594e+00 [46,] 1.609098e+00 -1.466701e+00 [47,] 7.399881e+00 1.609098e+00 [48,] 8.002514e+00 7.399881e+00 [49,] 1.176057e+01 8.002514e+00 [50,] 1.264596e+01 1.176057e+01 [51,] 1.266734e+01 1.264596e+01 [52,] 1.271910e+01 1.266734e+01 [53,] 1.147621e+01 1.271910e+01 [54,] 1.159897e+01 1.147621e+01 [55,] 1.111947e+01 1.159897e+01 [56,] 1.045910e+01 1.111947e+01 [57,] 1.417709e+01 1.045910e+01 [58,] 1.761960e+01 1.417709e+01 [59,] 1.416681e+01 1.761960e+01 [60,] 1.359756e+01 1.416681e+01 [61,] 9.241762e+00 1.359756e+01 [62,] 1.231888e+01 9.241762e+00 [63,] 1.221700e+01 1.231888e+01 [64,] 1.106487e+01 1.221700e+01 [65,] 1.053562e+01 1.106487e+01 [66,] 1.055775e+01 1.053562e+01 [67,] 9.104615e+00 1.055775e+01 [68,] 8.644866e+00 9.104615e+00 [69,] 1.534625e+01 8.644866e+00 [70,] 1.400587e+01 1.534625e+01 [71,] 1.230374e+01 1.400587e+01 [72,] 1.059010e+01 1.230374e+01 [73,] 8.896591e+00 1.059010e+01 [74,] 7.424835e+00 8.896591e+00 [75,] 1.039847e+01 7.424835e+00 [76,] 1.021747e+01 1.039847e+01 [77,] 9.116967e+00 1.021747e+01 [78,] 8.197092e+00 9.116967e+00 [79,] 6.293707e+00 8.197092e+00 [80,] 9.604961e+00 6.293707e+00 [81,] 9.872202e+00 9.604961e+00 [82,] 8.827688e+00 9.872202e+00 [83,] 8.078942e+00 8.827688e+00 [84,] 6.471920e+00 8.078942e+00 [85,] 3.433519e+00 6.471920e+00 [86,] 3.204773e+00 3.433519e+00 [87,] 2.922015e+00 3.204773e+00 [88,] 2.238880e+00 2.922015e+00 [89,] 5.829868e-01 2.238880e+00 [90,] -1.681527e+00 5.829868e-01 [91,] 6.784589e-02 -1.681527e+00 [92,] 2.647112e-01 6.784589e-02 [93,] -1.377922e+00 2.647112e-01 [94,] -1.758047e+00 -1.377922e+00 [95,] -1.240806e+00 -1.758047e+00 [96,] -2.632310e+00 -1.240806e+00 [97,] -4.926323e+00 -2.632310e+00 [98,] -3.568329e+00 -4.926323e+00 [99,] -6.468831e+00 -3.568329e+00 [100,] -8.969332e+00 -6.468831e+00 [101,] -7.391464e+00 -8.969332e+00 [102,] -9.453345e+00 -7.391464e+00 [103,] -9.518329e+00 -9.453345e+00 [104,] -7.288329e+00 -9.518329e+00 [105,] -9.441213e+00 -7.288329e+00 [106,] -5.781338e+00 -9.441213e+00 [107,] -3.403063e+00 -5.781338e+00 [108,] -3.880021e+00 -3.403063e+00 [109,] -1.948673e+01 -3.880021e+00 [110,] -1.090381e+01 -1.948673e+01 [111,] -7.396789e+00 -1.090381e+01 [112,] -5.173404e+00 -7.396789e+00 [113,] -5.200896e+00 -5.173404e+00 [114,] -4.553247e+00 -5.200896e+00 [115,] -1.987824e+00 -4.553247e+00 [116,] 2.165247e+00 -1.987824e+00 [117,] 1.545874e+00 2.165247e+00 [118,] 1.559856e+00 1.545874e+00 [119,] -8.966338e-04 1.559856e+00 [120,] -6.085142e-01 -8.966338e-04 [121,] 3.998868e-01 -6.085142e-01 [122,] 6.054040e-01 3.998868e-01 [123,] 2.035686e+00 6.054040e-01 [124,] 3.586469e+00 2.035686e+00 [125,] 2.736595e+00 3.586469e+00 [126,] 2.378852e+00 2.736595e+00 [127,] 4.189510e+00 2.378852e+00 [128,] 2.023115e+00 4.189510e+00 [129,] 1.633585e+00 2.023115e+00 [130,] 6.947127e+00 1.633585e+00 [131,] 6.939510e+00 6.947127e+00 [132,] 4.065341e+00 6.939510e+00 [133,] 5.943460e+00 4.065341e+00 [134,] 6.250106e+00 5.943460e+00 [135,] 4.798946e+00 6.250106e+00 [136,] 4.729699e+00 4.798946e+00 [137,] 3.570075e+00 4.729699e+00 [138,] 2.707960e-01 3.570075e+00 [139,] 1.746831e-01 2.707960e-01 [140,] -1.527950e+00 1.746831e-01 [141,] -5.613355e-01 -1.527950e+00 [142,] 2.702520e+00 -5.613355e-01 [143,] 3.268780e-01 2.702520e+00 [144,] -7.295168e-01 3.268780e-01 [145,] -6.362056e+00 -7.295168e-01 [146,] -6.811930e+00 -6.362056e+00 [147,] -2.592964e+00 -6.811930e+00 [148,] -5.680488e+00 -2.592964e+00 [149,] -4.932494e+00 -5.680488e+00 [150,] -7.161271e+00 -4.932494e+00 [151,] -6.986005e+00 -7.161271e+00 [152,] -6.288356e+00 -6.986005e+00 [153,] -4.802337e+00 -6.288356e+00 [154,] -1.769145e-01 -4.802337e+00 [155,] -2.782682e+00 -1.769145e-01 [156,] -3.881679e+00 -2.782682e+00 [157,] -7.079203e+00 -3.881679e+00 [158,] -2.821428e+00 -7.079203e+00 [159,] -3.921808e-01 -2.821428e+00 [160,] -3.630331e+00 -3.921808e-01 [161,] -6.366726e+00 -3.630331e+00 [162,] -1.012789e+01 -6.366726e+00 [163,] -1.076600e+01 -1.012789e+01 [164,] -4.367258e+00 -1.076600e+01 [165,] -5.289390e+00 -4.367258e+00 [166,] -4.090237e+00 -5.289390e+00 [167,] -5.411240e+00 -4.090237e+00 [168,] -6.763246e+00 -5.411240e+00 [169,] -8.648011e+00 -6.763246e+00 [170,] -5.039860e+00 -8.648011e+00 [171,] -2.235127e+00 -5.039860e+00 [172,] -1.990989e+00 -2.235127e+00 [173,] -2.710863e+00 -1.990989e+00 [174,] -1.934719e+00 -2.710863e+00 [175,] -6.160675e-01 -1.934719e+00 [176,] -1.103560e+00 -6.160675e-01 [177,] 2.931802e-01 -1.103560e+00 [178,] 7.258134e-01 2.931802e-01 [179,] 9.503274e-01 7.258134e-01 [180,] -2.965689e-01 9.503274e-01 [181,] -4.610581e+00 -2.965689e-01 [182,] -4.704939e+00 -4.610581e+00 [183,] -4.744061e+00 -4.704939e+00 [184,] -6.791584e+00 -4.744061e+00 [185,] -6.348700e+00 -6.791584e+00 [186,] -1.091359e+01 -6.348700e+00 [187,] -1.304021e+01 -1.091359e+01 [188,] -1.126218e+01 -1.304021e+01 [189,] -1.041804e+01 -1.126218e+01 [190,] -7.866883e+00 -1.041804e+01 [191,] -7.565002e+00 -7.866883e+00 [192,] -7.655002e+00 -7.565002e+00 [193,] -1.109905e+01 -7.655002e+00 [194,] -1.182180e+01 -1.109905e+01 [195,] -9.615189e+00 -1.182180e+01 [196,] -1.035133e+01 -9.615189e+00 [197,] -1.157522e+01 -1.035133e+01 [198,] -1.247861e+01 -1.157522e+01 [199,] -4.674092e+00 -1.247861e+01 [200,] -4.964719e+00 -4.674092e+00 [201,] -3.116443e+00 -4.964719e+00 [202,] -3.890205e+00 -3.116443e+00 [203,] -6.047603e+00 -3.890205e+00 [204,] -7.975377e+00 -6.047603e+00 [205,] -1.046756e+00 -7.975377e+00 [206,] 1.907349e+01 -1.046756e+00 [207,] 1.792186e+01 1.907349e+01 [208,] 1.655798e+01 1.792186e+01 [209,] 1.566857e+01 1.655798e+01 [210,] -7.946095e+00 1.566857e+01 [211,] -2.261042e+01 -7.946095e+00 [212,] -7.699163e+00 -2.261042e+01 [213,] -4.799665e+00 -7.699163e+00 [214,] -5.985182e+00 -4.799665e+00 [215,] -7.004148e+00 -5.985182e+00 [216,] -9.407659e+00 -7.004148e+00 [217,] -5.318599e+00 -9.407659e+00 [218,] -3.554305e+00 -5.318599e+00 [219,] -3.562800e+00 -3.554305e+00 [220,] 2.782651e-02 -3.562800e+00 [221,] -3.062675e+00 2.782651e-02 [222,] -4.010167e+00 -3.062675e+00 [223,] -8.344681e+00 -4.010167e+00 [224,] -8.109289e+00 -8.344681e+00 [225,] -7.364368e+00 -8.109289e+00 [226,] -5.659478e+00 -7.364368e+00 [227,] -3.833209e+00 -5.659478e+00 [228,] -4.822770e+00 -3.833209e+00 [229,] -2.565905e+00 -4.822770e+00 [230,] -1.762394e+00 -2.565905e+00 [231,] -3.961015e+00 -1.762394e+00 [232,] -6.621120e-01 -3.961015e+00 [233,] -1.592864e+00 -6.621120e-01 [234,] 2.902904e+00 -1.592864e+00 [235,] 1.844015e+01 2.902904e+00 [236,] 2.213579e+01 1.844015e+01 [237,] 2.438290e+01 2.213579e+01 [238,] 2.630905e+01 2.438290e+01 [239,] 1.787453e+01 2.630905e+01 [240,] 1.332391e+01 1.787453e+01 [241,] 3.188040e+01 1.332391e+01 [242,] 6.991432e+01 3.188040e+01 [243,] 4.850491e+01 6.991432e+01 [244,] 6.658645e+01 4.850491e+01 [245,] 5.708495e+01 6.658645e+01 [246,] 1.186836e+01 5.708495e+01 [247,] 3.991717e+00 1.186836e+01 [248,] 7.667327e-01 3.991717e+00 [249,] 1.863441e+00 7.667327e-01 [250,] -3.769045e-01 1.863441e+00 [251,] 1.131940e+01 -3.769045e-01 [252,] 1.524494e+01 1.131940e+01 [253,] 2.387996e+01 1.524494e+01 [254,] 7.060932e+00 2.387996e+01 [255,] 1.101871e+01 7.060932e+00 [256,] 2.017358e+00 1.101871e+01 [257,] 3.267389e+00 2.017358e+00 [258,] 4.757765e+00 3.267389e+00 [259,] 5.594662e+00 4.757765e+00 [260,] -2.463105e-01 5.594662e+00 [261,] 1.686855e+00 -2.463105e-01 [262,] 7.797984e+00 1.686855e+00 [263,] 1.001099e+01 7.797984e+00 [264,] 9.170868e+00 1.001099e+01 [265,] 6.520241e+00 9.170868e+00 [266,] 6.292718e+00 6.520241e+00 [267,] 5.162467e+00 6.292718e+00 [268,] 2.707326e+00 5.162467e+00 [269,] 5.045100e+00 2.707326e+00 [270,] -8.462792e-01 5.045100e+00 [271,] -3.588787e+00 -8.462792e-01 [272,] -6.685903e+00 -3.588787e+00 [273,] -9.348567e+00 -6.685903e+00 [274,] 3.908110e+00 -9.348567e+00 [275,] 1.588535e+01 3.908110e+00 [276,] 8.696463e-01 1.588535e+01 [277,] -8.299037e+00 8.696463e-01 [278,] -5.835024e+00 -8.299037e+00 [279,] -8.480385e+00 -5.835024e+00 [280,] -7.985244e+00 -8.480385e+00 [281,] -1.031421e+01 -7.985244e+00 [282,] -1.103759e+01 -1.031421e+01 [283,] -1.491885e+01 -1.103759e+01 [284,] -1.254719e+01 -1.491885e+01 [285,] -1.069593e+01 -1.254719e+01 [286,] -7.108160e+00 -1.069593e+01 [287,] -7.645777e+00 -7.108160e+00 [288,] -1.120879e+01 -7.645777e+00 [289,] -1.728941e+01 -1.120879e+01 [290,] -1.666941e+01 -1.728941e+01 [291,] -1.110126e+01 -1.666941e+01 [292,] -6.208881e+00 -1.110126e+01 [293,] -1.859778e+01 -6.208881e+00 [294,] -1.716189e+01 -1.859778e+01 [295,] -1.495700e+01 -1.716189e+01 [296,] -1.337587e+01 -1.495700e+01 [297,] -1.888612e+01 -1.337587e+01 [298,] -1.503424e+01 -1.888612e+01 [299,] -1.365634e+01 -1.503424e+01 [300,] -1.217073e+01 -1.365634e+01 [301,] -1.389349e+01 -1.217073e+01 [302,] -6.054085e+00 -1.389349e+01 [303,] -6.460260e+00 -6.054085e+00 [304,] -1.340615e+01 -6.460260e+00 [305,] -1.374850e+01 -1.340615e+01 [306,] -2.178490e+01 -1.374850e+01 [307,] -2.213039e+01 -2.178490e+01 [308,] -1.641089e+01 -2.213039e+01 [309,] -1.488625e+01 -1.641089e+01 [310,] -1.177901e+01 -1.488625e+01 [311,] -1.753499e+01 -1.177901e+01 [312,] -1.811669e+01 -1.753499e+01 [313,] -1.718879e+01 -1.811669e+01 [314,] -2.063142e+01 -1.718879e+01 [315,] -2.024233e+01 -2.063142e+01 [316,] -1.654493e+01 -2.024233e+01 [317,] -1.974568e+01 -1.654493e+01 [318,] -1.610882e+01 -1.974568e+01 [319,] -1.829744e+01 -1.610882e+01 [320,] -1.771869e+01 -1.829744e+01 [321,] -1.604841e+01 -1.771869e+01 [322,] -1.378415e+01 -1.604841e+01 [323,] -1.513769e+01 -1.378415e+01 [324,] -9.221325e+00 -1.513769e+01 [325,] -7.808315e+00 -9.221325e+00 [326,] -7.649349e+00 -7.808315e+00 [327,] -8.907845e+00 -7.649349e+00 [328,] -4.959695e+00 -8.907845e+00 [329,] 2.948957e+00 -4.959695e+00 [330,] -9.288597e+00 2.948957e+00 [331,] -8.260102e+00 -9.288597e+00 [332,] -1.291105e+00 -8.260102e+00 [333,] -1.368346e+00 -1.291105e+00 [334,] 8.757923e+00 -1.368346e+00 [335,] 1.849667e+01 8.757923e+00 [336,] 1.109093e+01 1.849667e+01 [337,] 2.810310e+01 1.109093e+01 [338,] 4.002294e+01 2.810310e+01 [339,] 2.566247e+01 4.002294e+01 [340,] 2.014981e+01 2.566247e+01 [341,] 1.072739e+01 2.014981e+01 [342,] 3.436170e+00 1.072739e+01 [343,] -1.033892e+00 3.436170e+00 [344,] -4.691008e+00 -1.033892e+00 [345,] 5.127487e+00 -4.691008e+00 [346,] 1.357529e+01 5.127487e+00 [347,] 1.544106e+01 1.357529e+01 [348,] 3.088993e+01 1.544106e+01 [349,] 2.327570e+01 3.088993e+01 [350,] 1.344827e+01 2.327570e+01 [351,] 1.493789e+01 1.344827e+01 [352,] 9.799243e+00 1.493789e+01 [353,] 8.611687e+00 9.799243e+00 [354,] 1.002068e+01 8.611687e+00 [355,] 1.493391e+01 1.002068e+01 [356,] 1.196529e+01 1.493391e+01 [357,] 1.164818e+01 1.196529e+01 [358,] 2.327416e+01 1.164818e+01 [359,] 3.245830e+01 2.327416e+01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 9.565960e+00 1.710906e+01 2 3.489754e+00 9.565960e+00 3 -8.471028e+00 3.489754e+00 4 -1.829642e+01 -8.471028e+00 5 -2.093212e+01 -1.829642e+01 6 -1.961824e+01 -2.093212e+01 7 -1.770034e+01 -1.961824e+01 8 -1.644369e+01 -1.770034e+01 9 -1.513742e+01 -1.644369e+01 10 -1.212438e+01 -1.513742e+01 11 -1.106924e+01 -1.212438e+01 12 -1.008372e+01 -1.106924e+01 13 -9.200714e+00 -1.008372e+01 14 -8.788959e+00 -9.200714e+00 15 -5.505417e+00 -8.788959e+00 16 -4.190150e+00 -5.505417e+00 17 -1.890872e+00 -4.190150e+00 18 -5.356053e-01 -1.890872e+00 19 3.671573e+00 -5.356053e-01 20 5.520601e+00 3.671573e+00 21 5.784613e+00 5.520601e+00 22 5.224237e+00 5.784613e+00 23 4.964613e+00 5.224237e+00 24 5.598501e+00 4.964613e+00 25 5.262137e+00 5.598501e+00 26 -1.970591e+00 5.262137e+00 27 -1.567707e+00 -1.970591e+00 28 3.431711e-01 -1.567707e+00 29 2.865773e+00 3.431711e-01 30 -1.863317e+00 2.865773e+00 31 -7.838175e+00 -1.863317e+00 32 -7.263222e+00 -7.838175e+00 33 -7.190870e+00 -7.263222e+00 34 -7.167767e+00 -7.190870e+00 35 -6.961779e+00 -7.167767e+00 36 -3.178363e+00 -6.961779e+00 37 -5.806889e+00 -3.178363e+00 38 -4.279616e+00 -5.806889e+00 39 1.755246e-01 -4.279616e+00 40 -1.518488e+00 1.755246e-01 41 -1.977109e+00 -1.518488e+00 42 -4.747265e+00 -1.977109e+00 43 -4.644883e+00 -4.747265e+00 44 -2.182594e+00 -4.644883e+00 45 -1.466701e+00 -2.182594e+00 46 1.609098e+00 -1.466701e+00 47 7.399881e+00 1.609098e+00 48 8.002514e+00 7.399881e+00 49 1.176057e+01 8.002514e+00 50 1.264596e+01 1.176057e+01 51 1.266734e+01 1.264596e+01 52 1.271910e+01 1.266734e+01 53 1.147621e+01 1.271910e+01 54 1.159897e+01 1.147621e+01 55 1.111947e+01 1.159897e+01 56 1.045910e+01 1.111947e+01 57 1.417709e+01 1.045910e+01 58 1.761960e+01 1.417709e+01 59 1.416681e+01 1.761960e+01 60 1.359756e+01 1.416681e+01 61 9.241762e+00 1.359756e+01 62 1.231888e+01 9.241762e+00 63 1.221700e+01 1.231888e+01 64 1.106487e+01 1.221700e+01 65 1.053562e+01 1.106487e+01 66 1.055775e+01 1.053562e+01 67 9.104615e+00 1.055775e+01 68 8.644866e+00 9.104615e+00 69 1.534625e+01 8.644866e+00 70 1.400587e+01 1.534625e+01 71 1.230374e+01 1.400587e+01 72 1.059010e+01 1.230374e+01 73 8.896591e+00 1.059010e+01 74 7.424835e+00 8.896591e+00 75 1.039847e+01 7.424835e+00 76 1.021747e+01 1.039847e+01 77 9.116967e+00 1.021747e+01 78 8.197092e+00 9.116967e+00 79 6.293707e+00 8.197092e+00 80 9.604961e+00 6.293707e+00 81 9.872202e+00 9.604961e+00 82 8.827688e+00 9.872202e+00 83 8.078942e+00 8.827688e+00 84 6.471920e+00 8.078942e+00 85 3.433519e+00 6.471920e+00 86 3.204773e+00 3.433519e+00 87 2.922015e+00 3.204773e+00 88 2.238880e+00 2.922015e+00 89 5.829868e-01 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1.863441e+00 7.667327e-01 250 -3.769045e-01 1.863441e+00 251 1.131940e+01 -3.769045e-01 252 1.524494e+01 1.131940e+01 253 2.387996e+01 1.524494e+01 254 7.060932e+00 2.387996e+01 255 1.101871e+01 7.060932e+00 256 2.017358e+00 1.101871e+01 257 3.267389e+00 2.017358e+00 258 4.757765e+00 3.267389e+00 259 5.594662e+00 4.757765e+00 260 -2.463105e-01 5.594662e+00 261 1.686855e+00 -2.463105e-01 262 7.797984e+00 1.686855e+00 263 1.001099e+01 7.797984e+00 264 9.170868e+00 1.001099e+01 265 6.520241e+00 9.170868e+00 266 6.292718e+00 6.520241e+00 267 5.162467e+00 6.292718e+00 268 2.707326e+00 5.162467e+00 269 5.045100e+00 2.707326e+00 270 -8.462792e-01 5.045100e+00 271 -3.588787e+00 -8.462792e-01 272 -6.685903e+00 -3.588787e+00 273 -9.348567e+00 -6.685903e+00 274 3.908110e+00 -9.348567e+00 275 1.588535e+01 3.908110e+00 276 8.696463e-01 1.588535e+01 277 -8.299037e+00 8.696463e-01 278 -5.835024e+00 -8.299037e+00 279 -8.480385e+00 -5.835024e+00 280 -7.985244e+00 -8.480385e+00 281 -1.031421e+01 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-1.753499e+01 313 -1.718879e+01 -1.811669e+01 314 -2.063142e+01 -1.718879e+01 315 -2.024233e+01 -2.063142e+01 316 -1.654493e+01 -2.024233e+01 317 -1.974568e+01 -1.654493e+01 318 -1.610882e+01 -1.974568e+01 319 -1.829744e+01 -1.610882e+01 320 -1.771869e+01 -1.829744e+01 321 -1.604841e+01 -1.771869e+01 322 -1.378415e+01 -1.604841e+01 323 -1.513769e+01 -1.378415e+01 324 -9.221325e+00 -1.513769e+01 325 -7.808315e+00 -9.221325e+00 326 -7.649349e+00 -7.808315e+00 327 -8.907845e+00 -7.649349e+00 328 -4.959695e+00 -8.907845e+00 329 2.948957e+00 -4.959695e+00 330 -9.288597e+00 2.948957e+00 331 -8.260102e+00 -9.288597e+00 332 -1.291105e+00 -8.260102e+00 333 -1.368346e+00 -1.291105e+00 334 8.757923e+00 -1.368346e+00 335 1.849667e+01 8.757923e+00 336 1.109093e+01 1.849667e+01 337 2.810310e+01 1.109093e+01 338 4.002294e+01 2.810310e+01 339 2.566247e+01 4.002294e+01 340 2.014981e+01 2.566247e+01 341 1.072739e+01 2.014981e+01 342 3.436170e+00 1.072739e+01 343 -1.033892e+00 3.436170e+00 344 -4.691008e+00 -1.033892e+00 345 5.127487e+00 -4.691008e+00 346 1.357529e+01 5.127487e+00 347 1.544106e+01 1.357529e+01 348 3.088993e+01 1.544106e+01 349 2.327570e+01 3.088993e+01 350 1.344827e+01 2.327570e+01 351 1.493789e+01 1.344827e+01 352 9.799243e+00 1.493789e+01 353 8.611687e+00 9.799243e+00 354 1.002068e+01 8.611687e+00 355 1.493391e+01 1.002068e+01 356 1.196529e+01 1.493391e+01 357 1.164818e+01 1.196529e+01 358 2.327416e+01 1.164818e+01 359 3.245830e+01 2.327416e+01 > 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/wessaorg/rcomp/tmp/7rkfr1321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/88qum1321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9tvps1321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10a8971321473905.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/wessaorg/rcomp/tmp/11pefm1321473905.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/wessaorg/rcomp/tmp/12vznl1321473905.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/wessaorg/rcomp/tmp/13x2361321473905.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/wessaorg/rcomp/tmp/144sev1321473905.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/wessaorg/rcomp/tmp/15duml1321473905.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/wessaorg/rcomp/tmp/16kh8e1321473905.tab") + } > > try(system("convert tmp/1e3021321473905.ps tmp/1e3021321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/2yfjg1321473905.ps tmp/2yfjg1321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/3xh581321473905.ps tmp/3xh581321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/4whj01321473905.ps tmp/4whj01321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/5pyfh1321473905.ps tmp/5pyfh1321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/681p81321473905.ps tmp/681p81321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/7rkfr1321473905.ps tmp/7rkfr1321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/88qum1321473905.ps tmp/88qum1321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/9tvps1321473905.ps tmp/9tvps1321473905.png",intern=TRUE)) character(0) > try(system("convert tmp/10a8971321473905.ps tmp/10a8971321473905.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 9.283 0.560 9.913