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Type 'q()' to quit R. > x <- array(list(-0.24 + ,0.13 + ,0.08 + ,-0.51 + ,0.10 + ,0.01 + ,0.78 + ,0.21 + ,0.08 + ,-0.30 + ,0.16 + ,0.02 + ,0.11 + ,0.12 + ,0.03 + ,1.37 + ,0.17 + ,0.05 + ,-0.07 + ,0.18 + ,0.03 + ,-0.23 + ,0.13 + ,0.01 + ,0.74 + ,0.20 + ,0.05 + ,0.14 + ,0.83 + ,0.04 + ,0.06 + ,0.83 + ,0.02 + ,-0.39 + ,0.80 + ,-0.02 + ,-0.15 + ,0.81 + ,-0.02 + ,0.11 + ,0.86 + ,0.01 + ,-0.23 + ,0.85 + ,-0.01 + ,-0.12 + ,0.86 + ,-0.06 + ,-0.12 + ,0.86 + ,-0.09 + ,-0.35 + ,0.83 + ,-0.05 + ,-0.45 + ,0.88 + ,-0.10 + ,-0.05 + ,0.87 + ,0.12 + ,-0.21 + ,0.91 + ,0.08 + ,0.20 + ,0.92 + ,0.10 + ,0.06 + ,0.93 + ,0.06 + ,-0.23 + ,0.73 + ,-0.01 + ,-0.10 + ,0.67 + ,0.02 + ,0.32 + ,0.67 + ,0.04 + ,0.12 + ,0.70 + ,0.00 + ,-0.30 + ,0.07 + ,0.01 + ,-0.15 + ,0.24 + ,0.08 + ,-0.41 + ,0.23 + ,0.06 + ,-0.23 + ,0.26 + ,0.04 + ,0.21 + ,0.37 + ,0.08 + ,0.40 + ,0.45 + ,0.06 + ,1.86 + ,0.49 + ,0.01 + ,-0.01 + ,0.53 + ,0.01 + ,0.07 + ,0.54 + ,0.06 + ,-0.46 + ,0.51 + ,-0.03 + ,-0.66 + ,0.37 + ,0.03 + ,0.45 + ,0.57 + 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,0.32 + ,0.79 + ,0.02 + ,-0.12 + ,0.75 + ,0.01 + ,-0.32 + ,0.76 + ,0.01 + ,99.2 + ,96.7 + ,101.0 + ,99.0 + ,98.1 + ,100.1 + ,100.0 + ,100.0 + ,100.0 + ,111.6 + ,104.9 + ,90.6 + ,122.2 + ,104.9 + ,86.5 + ,117.6 + ,109.5 + ,89.7 + ,121.1 + ,110.8 + ,90.6 + ,136.0 + ,112.3 + ,82.8 + ,154.2 + ,109.3 + ,70.1 + ,153.6 + ,105.3 + ,65.4 + ,158.5 + ,101.7 + ,61.3 + ,140.6 + ,95.4 + ,62.5 + ,136.2 + ,96.4 + ,63.6 + ,168.0 + ,97.6 + ,52.6 + ,154.3 + ,102.4 + ,59.7 + ,149.0 + ,101.6 + ,59.5 + ,165.5 + ,103.8 + ,61.3) + ,dim=c(3 + ,462) + ,dimnames=list(c('stock' + ,'asset' + ,'income') + ,1:462)) > y <- array(NA,dim=c(3,462),dimnames=list(c('stock','asset','income'),1:462)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par5 = '0' > par4 = '0' > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > par5 <- '0' > par4 <- '0' > par3 <- 'No Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Sun, 06 Dec 2015 16:18:54 +0000) > #Author: root > #To cite this work: Wessa P., (2015), Multiple Regression (v1.0.38) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > mywarning <- '' > par1 <- as.numeric(par1) > if(is.na(par1)) { + par1 <- 1 + mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.' + } > if (par4=='') par4 <- 0 > par4 <- as.numeric(par4) > if (par5=='') par5 <- 0 > par5 <- as.numeric(par5) > x <- na.omit(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'){ + (n <- n -1) + x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par3 == 'Seasonal Differences (s=12)'){ + (n <- n - 12) + x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep=''))) + for (i in 1:n) { + for (j in 1:k) { + x2[i,j] <- x[i+12,j] - x[i,j] + } + } + x <- x2 + } > if (par3 == 'First and Seasonal Differences (s=12)'){ + (n <- n -1) + x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + (n <- n - 12) + x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep=''))) + for (i in 1:n) { + for (j in 1:k) { + x2[i,j] <- x[i+12,j] - x[i,j] + } + } + x <- x2 + } > if(par4 > 0) { + x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep=''))) + for (i in 1:(n-par4)) { + for (j in 1:par4) { + x2[i,j] <- x[i+par4-j,par1] + } + } + x <- cbind(x[(par4+1):n,], x2) + n <- n - par4 + } > if(par5 > 0) { + x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep=''))) + for (i in 1:(n-par5*12)) { + for (j in 1:par5) { + x2[i,j] <- x[i+par5*12-j*12,par1] + } + } + x <- cbind(x[(par5*12+1):n,], x2) + n <- n - par5*12 + } > 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[n,])) [1] 3 > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x stock asset income 1 -0.24 0.13 0.08 2 -0.51 0.10 0.01 3 0.78 0.21 0.08 4 -0.30 0.16 0.02 5 0.11 0.12 0.03 6 1.37 0.17 0.05 7 -0.07 0.18 0.03 8 -0.23 0.13 0.01 9 0.74 0.20 0.05 10 0.14 0.83 0.04 11 0.06 0.83 0.02 12 -0.39 0.80 -0.02 13 -0.15 0.81 -0.02 14 0.11 0.86 0.01 15 -0.23 0.85 -0.01 16 -0.12 0.86 -0.06 17 -0.12 0.86 -0.09 18 -0.35 0.83 -0.05 19 -0.45 0.88 -0.10 20 -0.05 0.87 0.12 21 -0.21 0.91 0.08 22 0.20 0.92 0.10 23 0.06 0.93 0.06 24 -0.23 0.73 -0.01 25 -0.10 0.67 0.02 26 0.32 0.67 0.04 27 0.12 0.70 0.00 28 -0.30 0.07 0.01 29 -0.15 0.24 0.08 30 -0.41 0.23 0.06 31 -0.23 0.26 0.04 32 0.21 0.37 0.08 33 0.40 0.45 0.06 34 1.86 0.49 0.01 35 -0.01 0.53 0.01 36 0.07 0.54 0.06 37 -0.46 0.51 -0.03 38 -0.66 0.37 0.03 39 0.45 0.57 0.00 40 1.33 0.57 0.07 41 -0.34 0.55 0.05 42 -0.17 0.59 -0.03 43 1.21 0.60 0.02 44 -0.36 0.67 0.02 45 -0.14 0.62 0.02 46 -0.46 0.25 0.18 47 -0.65 0.18 0.19 48 0.98 0.21 0.18 49 0.68 0.25 0.23 50 -0.47 0.29 0.25 51 0.55 0.32 0.27 52 0.79 0.35 0.15 53 -0.41 0.42 0.09 54 -0.30 0.43 0.13 55 1.29 0.72 0.34 56 -0.75 0.68 0.10 57 0.22 0.76 0.08 58 -0.08 0.80 -0.16 59 -0.12 0.82 -0.27 60 -0.18 0.82 -0.41 61 0.08 0.84 -0.37 62 -0.38 0.85 -0.54 63 0.00 0.79 -1.02 64 -0.68 0.51 -0.21 65 -0.83 0.33 -0.46 66 4.62 0.34 -0.09 67 0.09 0.32 -0.02 68 0.41 0.49 0.05 69 1.55 0.78 0.09 70 1.93 0.74 0.08 71 -0.40 0.75 0.10 72 0.18 0.51 0.03 73 -0.12 0.53 0.03 74 0.20 0.57 0.03 75 0.45 0.59 0.04 76 0.01 0.25 0.03 77 0.44 0.29 0.03 78 0.03 0.30 0.03 79 0.19 0.31 0.03 80 0.20 0.35 0.04 81 0.11 0.67 0.13 82 -0.28 0.67 0.12 83 -0.25 0.70 0.09 84 0.95 0.71 0.13 85 0.15 0.70 0.15 86 0.26 0.69 0.17 87 -0.06 0.65 0.15 88 0.19 0.62 0.14 89 0.10 0.41 0.13 90 -0.12 0.80 0.18 91 -0.47 0.83 0.18 92 1.51 0.79 0.19 93 0.62 0.78 0.19 94 -0.12 0.72 0.19 95 0.15 0.74 0.19 96 0.37 0.75 0.19 97 0.04 0.67 0.18 98 0.14 0.71 0.17 99 0.41 0.73 0.15 100 -0.38 0.71 0.11 101 0.77 0.71 0.11 102 0.64 0.69 0.17 103 -0.11 0.67 0.19 104 0.08 0.65 0.15 105 -0.04 0.64 0.13 106 0.01 0.39 0.10 107 0.19 0.36 0.11 108 -0.35 0.73 0.06 109 -0.38 0.55 0.06 110 0.13 0.69 0.03 111 -0.15 0.72 0.00 112 -0.34 0.72 0.01 113 -0.14 0.68 -0.06 114 1.08 0.65 -0.02 115 0.25 0.40 -0.02 116 0.31 0.39 0.03 117 1.19 1.29 0.00 118 -0.32 2.20 -0.14 119 1.64 2.23 -0.22 120 0.76 1.90 0.10 121 -0.09 0.97 0.15 122 -0.38 0.27 -0.02 123 -0.02 0.30 -0.08 124 0.42 0.37 0.03 125 -0.33 2.10 -0.21 126 0.05 0.89 0.12 127 -0.28 0.85 0.10 128 -0.16 0.89 0.02 129 0.11 0.90 0.05 130 0.16 0.92 0.08 131 -0.08 0.92 0.06 132 -0.02 0.91 0.04 133 -0.25 0.91 0.00 134 0.57 0.92 0.03 135 1.58 0.75 -0.14 136 -0.61 0.71 -0.20 137 0.42 0.70 -0.30 138 -0.12 0.65 -0.27 139 -0.52 0.59 -0.07 140 -0.50 0.68 -0.08 141 -0.12 0.64 -0.27 142 -0.21 0.60 -0.39 143 -0.67 0.76 -0.35 144 -0.20 0.82 0.07 145 -0.75 0.56 0.01 146 1.41 0.69 -0.12 147 0.41 0.77 0.15 148 0.17 0.84 0.17 149 0.05 0.86 0.14 150 0.26 0.86 0.14 151 0.14 0.42 0.02 152 0.00 0.48 0.11 153 1.04 0.13 0.05 154 -0.25 0.20 0.06 155 0.57 0.30 0.06 156 0.25 0.34 0.05 157 -0.17 0.16 0.05 158 0.21 0.40 0.03 159 0.30 0.41 0.03 160 0.21 0.37 0.04 161 0.03 0.33 0.04 162 -0.89 0.18 -0.05 163 -0.74 0.19 -0.19 164 3.80 0.05 -0.20 165 0.41 0.16 -0.21 166 -0.05 0.27 -0.23 167 0.06 0.16 -0.53 168 0.72 0.34 0.06 169 -0.49 0.03 -0.01 170 -0.80 0.09 -0.06 171 0.78 0.71 0.29 172 -0.80 0.76 0.25 173 0.60 0.74 0.27 174 -0.02 0.76 0.24 175 0.31 0.73 0.20 176 0.02 0.73 0.22 177 0.15 0.75 0.22 178 0.15 0.73 0.24 179 -0.31 0.74 0.19 180 -0.20 0.49 -6.39 181 0.17 0.30 -4.03 182 -0.75 -0.15 -3.17 183 -0.37 0.81 0.23 184 0.27 0.91 -4.45 185 0.03 0.64 0.12 186 -0.40 0.55 0.09 187 -0.29 0.58 0.09 188 0.56 0.63 0.09 189 0.53 0.64 0.11 190 0.51 0.65 0.13 191 0.09 0.63 0.14 192 0.13 0.73 0.13 193 -0.22 0.72 0.13 194 0.53 0.42 0.16 195 -0.16 0.60 0.19 196 0.21 0.60 0.19 197 1.06 0.65 0.23 198 -0.52 0.49 0.19 199 0.80 0.51 0.17 200 1.02 0.51 0.09 201 0.71 0.44 0.28 202 0.02 0.51 0.28 203 0.04 0.90 -0.02 204 -0.44 0.91 0.02 205 -0.44 0.82 -1.57 206 0.26 0.80 -0.07 207 0.21 0.82 0.12 208 -0.03 0.86 0.04 209 0.04 0.86 -0.02 210 0.60 0.88 0.06 211 0.66 0.86 0.19 212 -0.31 0.82 -0.04 213 -0.70 0.72 -0.04 214 -0.15 0.54 -0.08 215 0.20 0.51 -0.02 216 0.14 0.59 -0.02 217 0.29 0.61 -0.03 218 -0.14 0.53 -0.19 219 -0.13 0.70 -0.28 220 -0.27 0.60 -0.24 221 1.36 0.67 0.08 222 -0.21 0.67 0.08 223 -0.53 0.64 -0.01 224 0.15 0.62 0.05 225 -0.13 0.62 0.02 226 -0.14 0.69 0.01 227 0.43 0.64 0.04 228 -0.04 0.69 -0.07 229 -0.11 0.64 -0.07 230 0.62 0.79 0.04 231 -0.41 0.77 0.06 232 -0.16 0.83 0.05 233 -0.09 0.66 0.03 234 -0.06 0.67 0.03 235 0.21 0.55 0.05 236 0.96 0.62 0.06 237 -0.13 0.65 0.04 238 0.19 0.64 0.03 239 0.05 0.75 0.10 240 -0.55 0.81 0.06 241 -0.33 0.85 -0.06 242 -0.10 0.83 0.01 243 0.63 0.86 0.06 244 -0.10 0.85 0.02 245 0.14 0.84 0.00 246 -0.01 0.81 0.01 247 0.17 0.78 0.02 248 0.07 0.38 0.04 249 -0.59 0.35 0.04 250 1.14 0.39 0.05 251 0.25 0.35 0.04 252 -0.12 0.32 0.04 253 -0.10 0.35 0.05 254 0.38 0.24 0.05 255 -0.37 0.32 0.04 256 -0.19 0.29 0.07 257 -0.21 0.47 -0.15 258 -0.38 0.43 -0.02 259 0.23 0.66 0.04 260 0.27 0.80 0.09 261 0.59 0.85 0.11 262 -0.31 0.86 0.12 263 -0.29 0.88 -0.13 264 0.23 0.88 -0.04 265 0.29 0.90 0.08 266 -0.31 0.45 0.34 267 -0.22 0.36 0.34 268 -0.02 0.40 0.28 269 0.40 0.42 0.27 270 -0.11 0.44 0.26 271 0.19 0.47 0.25 272 0.98 0.51 0.16 273 -0.02 0.41 0.22 274 -0.23 0.39 0.07 275 0.18 0.77 0.14 276 -0.07 0.83 0.13 277 -0.04 0.84 0.13 278 0.17 0.83 0.15 279 0.12 0.72 0.05 280 0.23 0.65 0.15 281 1.01 0.69 0.17 282 0.15 0.78 0.14 283 0.51 -0.71 0.20 284 0.97 -0.13 0.14 285 -0.94 -0.26 0.14 286 6.94 -0.28 0.03 287 0.48 -0.29 0.22 288 0.31 -0.32 0.16 289 0.35 0.00 0.26 290 4.26 -0.01 0.21 291 -0.07 0.04 0.27 292 0.13 0.05 0.23 293 0.46 0.48 -0.02 294 -0.60 0.44 -0.18 295 1.30 0.39 -0.02 296 -0.41 0.40 -0.03 297 -0.38 0.50 0.04 298 0.29 0.53 0.00 299 0.35 0.34 -0.03 300 0.01 0.32 -0.03 301 -0.26 0.27 -0.02 302 0.46 0.47 0.06 303 0.25 0.45 0.07 304 -0.45 0.34 0.06 305 0.51 0.36 0.06 306 0.09 0.40 0.06 307 0.20 0.40 0.05 308 0.63 0.30 0.07 309 0.15 0.31 0.09 310 0.22 0.36 0.09 311 0.23 0.81 0.03 312 -0.12 0.80 0.03 313 -0.61 0.85 -0.06 314 0.28 0.83 -0.07 315 0.45 0.79 0.07 316 -0.14 0.78 0.10 317 0.43 0.77 0.11 318 0.62 0.78 0.05 319 -0.17 0.64 0.00 320 -0.99 0.38 0.46 321 -0.52 0.30 0.47 322 0.58 0.28 0.50 323 0.40 0.27 0.43 324 -0.07 0.30 0.47 325 0.02 0.22 0.47 326 0.00 0.27 0.41 327 -0.04 0.28 0.18 328 -0.15 0.28 0.39 329 -0.65 0.38 0.31 330 -0.81 0.28 0.24 331 5.73 0.24 -0.02 332 -0.62 0.23 0.05 333 -0.17 0.29 0.07 334 -0.24 0.25 0.17 335 4.28 0.21 0.16 336 -0.57 0.17 0.17 337 0.01 -0.04 0.08 338 -0.17 0.43 0.27 339 -0.61 0.47 0.19 340 1.53 0.56 0.23 341 -0.09 0.39 0.11 342 0.27 0.37 0.03 343 -0.14 0.42 0.06 344 0.33 0.53 0.03 345 0.31 0.58 0.01 346 0.10 0.69 0.25 347 0.20 0.78 -0.08 348 -0.30 0.76 -0.04 349 -0.16 0.74 0.05 350 0.09 0.67 0.01 351 0.28 0.69 0.01 352 -0.13 0.71 -0.01 353 0.55 0.76 -0.03 354 0.07 0.80 -0.01 355 -0.41 0.81 -0.23 356 0.64 0.83 0.16 357 -0.58 0.83 0.17 358 0.60 0.85 0.06 359 0.89 0.85 0.11 360 -0.07 0.83 0.19 361 1.64 0.91 0.08 362 0.68 0.90 -0.06 363 -0.38 0.87 -0.20 364 -0.72 0.84 -1.97 365 0.44 0.76 0.19 366 -0.40 0.77 0.24 367 0.65 0.85 0.30 368 0.26 0.83 0.23 369 -0.02 0.83 0.22 370 0.15 0.78 0.29 371 0.70 0.72 0.32 372 -0.01 0.77 0.29 373 0.01 0.81 0.29 374 -0.15 0.68 0.09 375 -0.36 0.58 0.07 376 0.59 0.64 0.08 377 0.49 0.71 0.09 378 -0.13 0.67 0.09 379 0.11 0.67 0.09 380 0.65 0.68 0.08 381 0.22 0.65 0.08 382 0.07 0.66 0.08 383 -0.38 0.86 0.20 384 -0.42 0.83 0.13 385 -0.46 0.87 -0.53 386 -0.07 0.83 -3.07 387 -0.02 0.77 -3.61 388 -0.59 0.67 -3.72 389 -0.29 0.35 -4.72 390 -0.27 0.38 -5.30 391 1.12 -0.12 -7.03 392 0.03 0.66 0.09 393 -0.55 0.61 0.10 394 1.21 0.63 0.03 395 0.29 0.47 0.11 396 -0.27 0.53 0.06 397 -0.16 0.45 -0.11 398 -0.07 0.42 0.05 399 -0.12 0.45 0.04 400 -0.10 0.31 0.03 401 -0.11 0.75 0.13 402 0.19 0.75 0.15 403 -0.46 0.79 0.16 404 1.03 0.79 0.17 405 0.07 0.79 0.18 406 -0.22 0.72 0.12 407 0.62 0.75 0.13 408 -0.16 0.76 0.14 409 -0.03 0.70 0.11 410 -0.34 0.88 -7.30 411 -0.67 0.82 -4.69 412 1.33 0.82 -2.25 413 -0.39 0.88 -3.58 414 1.18 0.88 -0.26 415 -0.34 0.92 -1.34 416 -0.59 0.93 -4.06 417 -0.11 0.90 -1.09 418 -0.61 0.91 -0.45 419 -0.09 0.78 0.10 420 -0.48 0.82 0.08 421 0.38 0.84 0.06 422 -0.01 0.84 0.12 423 -0.03 0.85 0.16 424 0.23 0.85 0.11 425 1.03 0.78 0.13 426 0.25 0.63 0.03 427 -0.34 0.64 -0.96 428 -0.43 0.25 0.01 429 -0.23 0.20 0.03 430 -0.17 0.17 0.00 431 0.47 0.20 0.03 432 -0.44 0.23 0.03 433 0.27 0.30 0.02 434 1.06 0.36 0.03 435 0.23 0.38 0.03 436 -0.01 0.44 0.03 437 -0.48 0.61 0.01 438 -0.49 0.60 -0.03 439 0.77 0.70 0.02 440 0.31 0.72 0.02 441 0.10 0.76 0.03 442 -0.08 0.78 0.04 443 0.32 0.79 0.02 444 -0.12 0.75 0.01 445 -0.32 0.76 0.01 446 99.20 96.70 101.00 447 99.00 98.10 100.10 448 100.00 100.00 100.00 449 111.60 104.90 90.60 450 122.20 104.90 86.50 451 117.60 109.50 89.70 452 121.10 110.80 90.60 453 136.00 112.30 82.80 454 154.20 109.30 70.10 455 153.60 105.30 65.40 456 158.50 101.70 61.30 457 140.60 95.40 62.50 458 136.20 96.40 63.60 459 168.00 97.60 52.60 460 154.30 102.40 59.70 461 149.00 101.60 59.50 462 165.50 103.80 61.30 > (k <- length(x[n,])) [1] 3 > head(x) stock asset income 1 -0.24 0.13 0.08 2 -0.51 0.10 0.01 3 0.78 0.21 0.08 4 -0.30 0.16 0.02 5 0.11 0.12 0.03 6 1.37 0.17 0.05 > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) asset income -1.296 2.233 -1.239 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -14.4943 -0.4833 0.0625 0.6712 16.5261 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.29637 0.10915 -11.88 <2e-16 *** asset 2.23276 0.02491 89.62 <2e-16 *** income -1.23853 0.03260 -37.99 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 2.257 on 459 degrees of freedom Multiple R-squared: 0.9923, Adjusted R-squared: 0.9923 F-statistic: 2.967e+04 on 2 and 459 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,] 3.409916e-02 6.819832e-02 0.9659008 [2,] 1.123067e-02 2.246134e-02 0.9887693 [3,] 2.660412e-03 5.320824e-03 0.9973396 [4,] 5.944152e-04 1.188830e-03 0.9994056 [5,] 4.071291e-04 8.142582e-04 0.9995929 [6,] 9.350713e-05 1.870143e-04 0.9999065 [7,] 2.036783e-05 4.073567e-05 0.9999796 [8,] 4.637104e-06 9.274208e-06 0.9999954 [9,] 9.401047e-07 1.880209e-06 0.9999991 [10,] 1.805492e-07 3.610983e-07 0.9999998 [11,] 6.084077e-08 1.216815e-07 0.9999999 [12,] 2.037393e-08 4.074785e-08 1.0000000 [13,] 3.895123e-09 7.790246e-09 1.0000000 [14,] 7.324962e-10 1.464992e-09 1.0000000 [15,] 2.851399e-10 5.702799e-10 1.0000000 [16,] 7.100164e-11 1.420033e-10 1.0000000 [17,] 1.278602e-11 2.557204e-11 1.0000000 [18,] 2.233504e-12 4.467007e-12 1.0000000 [19,] 3.962435e-13 7.924870e-13 1.0000000 [20,] 6.737139e-14 1.347428e-13 1.0000000 [21,] 1.408559e-14 2.817118e-14 1.0000000 [22,] 2.565253e-15 5.130507e-15 1.0000000 [23,] 6.649819e-16 1.329964e-15 1.0000000 [24,] 1.707162e-16 3.414324e-16 1.0000000 [25,] 7.196052e-17 1.439210e-16 1.0000000 [26,] 1.492770e-17 2.985540e-17 1.0000000 [27,] 2.437215e-18 4.874430e-18 1.0000000 [28,] 5.389927e-19 1.077985e-18 1.0000000 [29,] 7.757145e-16 1.551429e-15 1.0000000 [30,] 1.617710e-16 3.235420e-16 1.0000000 [31,] 3.343002e-17 6.686003e-17 1.0000000 [32,] 8.938868e-18 1.787774e-17 1.0000000 [33,] 5.119191e-18 1.023838e-17 1.0000000 [34,] 1.706522e-18 3.413045e-18 1.0000000 [35,] 4.514067e-18 9.028134e-18 1.0000000 [36,] 1.457985e-18 2.915969e-18 1.0000000 [37,] 3.153266e-19 6.306533e-19 1.0000000 [38,] 7.292253e-19 1.458451e-18 1.0000000 [39,] 2.176242e-19 4.352484e-19 1.0000000 [40,] 5.127769e-20 1.025554e-19 1.0000000 [41,] 4.204624e-20 8.409247e-20 1.0000000 [42,] 3.365858e-20 6.731716e-20 1.0000000 [43,] 2.041765e-20 4.083530e-20 1.0000000 [44,] 5.600719e-21 1.120144e-20 1.0000000 [45,] 3.604792e-21 7.209584e-21 1.0000000 [46,] 9.332927e-22 1.866585e-21 1.0000000 [47,] 3.726523e-22 7.453046e-22 1.0000000 [48,] 1.342261e-22 2.684522e-22 1.0000000 [49,] 4.313587e-23 8.627174e-23 1.0000000 [50,] 2.390349e-23 4.780698e-23 1.0000000 [51,] 1.989186e-23 3.978373e-23 1.0000000 [52,] 4.707290e-24 9.414581e-24 1.0000000 [53,] 1.171021e-24 2.342042e-24 1.0000000 [54,] 3.138565e-25 6.277130e-25 1.0000000 [55,] 8.888160e-26 1.777632e-25 1.0000000 [56,] 2.839661e-26 5.679322e-26 1.0000000 [57,] 6.731625e-27 1.346325e-26 1.0000000 [58,] 3.129905e-27 6.259810e-27 1.0000000 [59,] 1.285967e-27 2.571935e-27 1.0000000 [60,] 4.860331e-28 9.720662e-28 1.0000000 [61,] 4.534308e-19 9.068617e-19 1.0000000 [62,] 1.490516e-19 2.981032e-19 1.0000000 [63,] 5.128807e-20 1.025761e-19 1.0000000 [64,] 7.259202e-20 1.451840e-19 1.0000000 [65,] 2.005529e-19 4.011058e-19 1.0000000 [66,] 8.559177e-20 1.711835e-19 1.0000000 [67,] 2.866566e-20 5.733132e-20 1.0000000 [68,] 1.000671e-20 2.001341e-20 1.0000000 [69,] 3.299401e-21 6.598802e-21 1.0000000 [70,] 1.144822e-21 2.289644e-21 1.0000000 [71,] 3.815348e-22 7.630696e-22 1.0000000 [72,] 1.317294e-22 2.634588e-22 1.0000000 [73,] 4.303466e-23 8.606932e-23 1.0000000 [74,] 1.380006e-23 2.760012e-23 1.0000000 [75,] 4.386054e-24 8.772107e-24 1.0000000 [76,] 1.379959e-24 2.759917e-24 1.0000000 [77,] 5.103479e-25 1.020696e-24 1.0000000 [78,] 1.805682e-25 3.611364e-25 1.0000000 [79,] 8.729064e-26 1.745813e-25 1.0000000 [80,] 2.682681e-26 5.365362e-26 1.0000000 [81,] 8.170729e-27 1.634146e-26 1.0000000 [82,] 2.622565e-27 5.245129e-27 1.0000000 [83,] 7.880828e-28 1.576166e-27 1.0000000 [84,] 2.393316e-28 4.786631e-28 1.0000000 [85,] 7.773264e-29 1.554653e-28 1.0000000 [86,] 3.322584e-29 6.645168e-29 1.0000000 [87,] 4.092923e-29 8.185846e-29 1.0000000 [88,] 1.371640e-29 2.743280e-29 1.0000000 [89,] 4.519871e-30 9.039742e-30 1.0000000 [90,] 1.334880e-30 2.669759e-30 1.0000000 [91,] 3.955749e-31 7.911499e-31 1.0000000 [92,] 1.183944e-31 2.367888e-31 1.0000000 [93,] 3.429262e-32 6.858524e-32 1.0000000 [94,] 1.016821e-32 2.033641e-32 1.0000000 [95,] 3.857320e-33 7.714639e-33 1.0000000 [96,] 1.490753e-33 2.981507e-33 1.0000000 [97,] 4.928613e-34 9.857227e-34 1.0000000 [98,] 1.552892e-34 3.105784e-34 1.0000000 [99,] 4.423306e-35 8.846612e-35 1.0000000 [100,] 1.299309e-35 2.598618e-35 1.0000000 [101,] 3.742613e-36 7.485225e-36 1.0000000 [102,] 1.046498e-36 2.092996e-36 1.0000000 [103,] 3.653020e-37 7.306039e-37 1.0000000 [104,] 1.309711e-37 2.619421e-37 1.0000000 [105,] 3.554334e-38 7.108668e-38 1.0000000 [106,] 1.026656e-38 2.053312e-38 1.0000000 [107,] 3.379807e-39 6.759613e-39 1.0000000 [108,] 9.460062e-40 1.892012e-39 1.0000000 [109,] 6.571400e-40 1.314280e-39 1.0000000 [110,] 1.800992e-40 3.601985e-40 1.0000000 [111,] 4.976277e-41 9.952553e-41 1.0000000 [112,] 4.087180e-41 8.174360e-41 1.0000000 [113,] 1.825723e-41 3.651445e-41 1.0000000 [114,] 4.546139e-41 9.092277e-41 1.0000000 [115,] 1.460920e-41 2.921840e-41 1.0000000 [116,] 4.607983e-42 9.215967e-42 1.0000000 [117,] 1.485372e-42 2.970744e-42 1.0000000 [118,] 3.989739e-43 7.979479e-43 1.0000000 [119,] 1.190795e-43 2.381591e-43 1.0000000 [120,] 6.889802e-44 1.377960e-43 1.0000000 [121,] 1.898168e-44 3.796336e-44 1.0000000 [122,] 6.504817e-45 1.300963e-44 1.0000000 [123,] 1.943925e-45 3.887851e-45 1.0000000 [124,] 5.135132e-46 1.027026e-45 1.0000000 [125,] 1.341781e-46 2.683563e-46 1.0000000 [126,] 3.804839e-47 7.609678e-47 1.0000000 [127,] 1.032581e-47 2.065162e-47 1.0000000 [128,] 3.222552e-48 6.445104e-48 1.0000000 [129,] 9.605314e-49 1.921063e-48 1.0000000 [130,] 2.513443e-48 5.026885e-48 1.0000000 [131,] 1.042493e-48 2.084986e-48 1.0000000 [132,] 3.193790e-49 6.387579e-49 1.0000000 [133,] 8.395878e-50 1.679176e-49 1.0000000 [134,] 3.185391e-50 6.370782e-50 1.0000000 [135,] 1.188019e-50 2.376039e-50 1.0000000 [136,] 3.075273e-51 6.150546e-51 1.0000000 [137,] 8.000977e-52 1.600195e-51 1.0000000 [138,] 3.175885e-52 6.351770e-52 1.0000000 [139,] 9.415011e-53 1.883002e-52 1.0000000 [140,] 5.177854e-53 1.035571e-52 1.0000000 [141,] 8.745224e-53 1.749045e-52 1.0000000 [142,] 2.284829e-53 4.569658e-53 1.0000000 [143,] 5.772482e-54 1.154496e-53 1.0000000 [144,] 1.497626e-54 2.995252e-54 1.0000000 [145,] 3.727910e-55 7.455820e-55 1.0000000 [146,] 9.309554e-56 1.861911e-55 1.0000000 [147,] 2.364419e-56 4.728837e-56 1.0000000 [148,] 1.732866e-56 3.465733e-56 1.0000000 [149,] 4.958151e-57 9.916303e-57 1.0000000 [150,] 1.583614e-57 3.167228e-57 1.0000000 [151,] 4.026923e-58 8.053847e-58 1.0000000 [152,] 1.085555e-58 2.171111e-58 1.0000000 [153,] 2.689830e-59 5.379661e-59 1.0000000 [154,] 6.831165e-60 1.366233e-59 1.0000000 [155,] 1.683213e-60 3.366425e-60 1.0000000 [156,] 4.112403e-61 8.224805e-61 1.0000000 [157,] 2.549250e-61 5.098500e-61 1.0000000 [158,] 1.016398e-61 2.032796e-61 1.0000000 [159,] 8.965998e-56 1.793200e-55 1.0000000 [160,] 2.733600e-56 5.467200e-56 1.0000000 [161,] 7.266451e-57 1.453290e-56 1.0000000 [162,] 1.916352e-57 3.832704e-57 1.0000000 [163,] 7.006588e-58 1.401318e-57 1.0000000 [164,] 2.642886e-58 5.285771e-58 1.0000000 [165,] 1.433476e-58 2.866952e-58 1.0000000 [166,] 4.875942e-59 9.751884e-59 1.0000000 [167,] 3.410909e-59 6.821818e-59 1.0000000 [168,] 1.002181e-59 2.004362e-59 1.0000000 [169,] 2.721658e-60 5.443317e-60 1.0000000 [170,] 7.029502e-61 1.405900e-60 1.0000000 [171,] 1.854077e-61 3.708154e-61 1.0000000 [172,] 4.715030e-62 9.430059e-62 1.0000000 [173,] 1.195373e-62 2.390747e-62 1.0000000 [174,] 3.855013e-63 7.710026e-63 1.0000000 [175,] 1.416680e-62 2.833360e-62 1.0000000 [176,] 7.886806e-63 1.577361e-62 1.0000000 [177,] 4.213000e-63 8.426000e-63 1.0000000 [178,] 1.418813e-63 2.837626e-63 1.0000000 [179,] 1.912236e-63 3.824472e-63 1.0000000 [180,] 4.919393e-64 9.838786e-64 1.0000000 [181,] 1.642799e-64 3.285598e-64 1.0000000 [182,] 4.937769e-65 9.875539e-65 1.0000000 [183,] 1.485673e-65 2.971347e-65 1.0000000 [184,] 4.337662e-66 8.675324e-66 1.0000000 [185,] 1.240417e-66 2.480835e-66 1.0000000 [186,] 3.095770e-67 6.191539e-67 1.0000000 [187,] 7.661591e-68 1.532318e-67 1.0000000 [188,] 2.172743e-68 4.345486e-68 1.0000000 [189,] 6.525651e-69 1.305130e-68 1.0000000 [190,] 1.754436e-69 3.508872e-69 1.0000000 [191,] 4.321073e-70 8.642147e-70 1.0000000 [192,] 2.508459e-70 5.016919e-70 1.0000000 [193,] 9.457423e-71 1.891485e-70 1.0000000 [194,] 3.720588e-71 7.441176e-71 1.0000000 [195,] 2.066173e-71 4.132346e-71 1.0000000 [196,] 7.361461e-72 1.472292e-71 1.0000000 [197,] 1.839141e-72 3.678281e-72 1.0000000 [198,] 4.573950e-73 9.147900e-73 1.0000000 [199,] 1.660628e-73 3.321255e-73 1.0000000 [200,] 7.447087e-74 1.489417e-73 1.0000000 [201,] 1.807670e-74 3.615341e-74 1.0000000 [202,] 4.307794e-75 8.615587e-75 1.0000000 [203,] 1.071552e-75 2.143103e-75 1.0000000 [204,] 2.597159e-76 5.194318e-76 1.0000000 [205,] 7.447962e-77 1.489592e-76 1.0000000 [206,] 2.236658e-77 4.473316e-77 1.0000000 [207,] 6.734265e-78 1.346853e-77 1.0000000 [208,] 3.437249e-78 6.874499e-78 1.0000000 [209,] 8.675510e-79 1.735102e-78 1.0000000 [210,] 2.024947e-79 4.049894e-79 1.0000000 [211,] 4.662987e-80 9.325973e-80 1.0000000 [212,] 1.096337e-80 2.192673e-80 1.0000000 [213,] 2.701426e-81 5.402853e-81 1.0000000 [214,] 6.749188e-82 1.349838e-81 1.0000000 [215,] 1.829216e-82 3.658432e-82 1.0000000 [216,] 2.101187e-82 4.202374e-82 1.0000000 [217,] 5.480261e-83 1.096052e-82 1.0000000 [218,] 2.029320e-83 4.058640e-83 1.0000000 [219,] 4.574010e-84 9.148019e-84 1.0000000 [220,] 1.109928e-84 2.219855e-84 1.0000000 [221,] 2.713710e-85 5.427420e-85 1.0000000 [222,] 6.641656e-86 1.328331e-85 1.0000000 [223,] 1.531520e-86 3.063041e-86 1.0000000 [224,] 3.619825e-87 7.239650e-87 1.0000000 [225,] 1.017246e-87 2.034492e-87 1.0000000 [226,] 3.211026e-88 6.422052e-88 1.0000000 [227,] 7.942531e-89 1.588506e-88 1.0000000 [228,] 1.834371e-89 3.668742e-89 1.0000000 [229,] 4.160124e-90 8.320248e-90 1.0000000 [230,] 9.089187e-91 1.817837e-90 1.0000000 [231,] 4.297772e-91 8.595545e-91 1.0000000 [232,] 1.003140e-91 2.006281e-91 1.0000000 [233,] 2.153507e-92 4.307014e-92 1.0000000 [234,] 4.646054e-93 9.292108e-93 1.0000000 [235,] 1.772792e-93 3.545583e-93 1.0000000 [236,] 5.034200e-94 1.006840e-93 1.0000000 [237,] 1.157363e-94 2.314725e-94 1.0000000 [238,] 3.193113e-95 6.386226e-95 1.0000000 [239,] 7.323406e-96 1.464681e-95 1.0000000 [240,] 1.548331e-96 3.096663e-96 1.0000000 [241,] 3.349255e-97 6.698509e-97 1.0000000 [242,] 6.975875e-98 1.395175e-97 1.0000000 [243,] 1.467433e-98 2.934867e-98 1.0000000 [244,] 5.417983e-99 1.083597e-98 1.0000000 [245,] 4.125309e-99 8.250618e-99 1.0000000 [246,] 8.919352e-100 1.783870e-99 1.0000000 [247,] 1.985420e-100 3.970840e-100 1.0000000 [248,] 4.345328e-101 8.690656e-101 1.0000000 [249,] 1.029698e-101 2.059397e-101 1.0000000 [250,] 2.777643e-102 5.555286e-102 1.0000000 [251,] 6.386357e-103 1.277271e-102 1.0000000 [252,] 1.444751e-103 2.889502e-103 1.0000000 [253,] 3.850697e-104 7.701394e-104 1.0000000 [254,] 7.760198e-105 1.552040e-104 1.0000000 [255,] 1.571147e-105 3.142295e-105 1.0000000 [256,] 3.929678e-106 7.859356e-106 1.0000000 [257,] 1.021130e-106 2.042261e-106 1.0000000 [258,] 2.642215e-107 5.284430e-107 1.0000000 [259,] 5.309947e-108 1.061989e-107 1.0000000 [260,] 1.069301e-108 2.138603e-108 1.0000000 [261,] 2.673656e-109 5.347312e-109 1.0000000 [262,] 6.196130e-110 1.239226e-109 1.0000000 [263,] 1.266234e-110 2.532468e-110 1.0000000 [264,] 2.844284e-111 5.688569e-111 1.0000000 [265,] 5.931554e-112 1.186311e-111 1.0000000 [266,] 1.171996e-112 2.343991e-112 1.0000000 [267,] 5.957105e-113 1.191421e-112 1.0000000 [268,] 1.190147e-113 2.380294e-113 1.0000000 [269,] 2.613444e-114 5.226888e-114 1.0000000 [270,] 4.908414e-115 9.816827e-115 1.0000000 [271,] 9.785217e-116 1.957043e-115 1.0000000 [272,] 1.914072e-116 3.828143e-116 1.0000000 [273,] 3.552027e-117 7.104053e-117 1.0000000 [274,] 6.544956e-118 1.308991e-117 1.0000000 [275,] 1.219235e-118 2.438471e-118 1.0000000 [276,] 6.102997e-119 1.220599e-118 1.0000000 [277,] 1.113357e-119 2.226714e-119 1.0000000 [278,] 6.119840e-120 1.223968e-119 1.0000000 [279,] 4.446837e-120 8.893674e-120 1.0000000 [280,] 3.667816e-120 7.335631e-120 1.0000000 [281,] 9.887707e-99 1.977541e-98 1.0000000 [282,] 3.863035e-99 7.726071e-99 1.0000000 [283,] 1.401099e-99 2.802198e-99 1.0000000 [284,] 4.256939e-100 8.513877e-100 1.0000000 [285,] 2.638869e-94 5.277738e-94 1.0000000 [286,] 8.502789e-95 1.700558e-94 1.0000000 [287,] 2.569735e-95 5.139470e-95 1.0000000 [288,] 6.600744e-96 1.320149e-95 1.0000000 [289,] 2.423929e-96 4.847858e-96 1.0000000 [290,] 1.764360e-96 3.528719e-96 1.0000000 [291,] 5.408461e-97 1.081692e-96 1.0000000 [292,] 1.572991e-97 3.145982e-97 1.0000000 [293,] 3.709529e-98 7.419058e-98 1.0000000 [294,] 9.256898e-99 1.851380e-98 1.0000000 [295,] 2.265428e-99 4.530856e-99 1.0000000 [296,] 6.353719e-100 1.270744e-99 1.0000000 [297,] 1.619591e-100 3.239181e-100 1.0000000 [298,] 3.824339e-101 7.648677e-101 1.0000000 [299,] 1.223681e-101 2.447363e-101 1.0000000 [300,] 3.301172e-102 6.602343e-102 1.0000000 [301,] 7.744246e-103 1.548849e-102 1.0000000 [302,] 1.813658e-103 3.627316e-103 1.0000000 [303,] 5.465281e-104 1.093056e-103 1.0000000 [304,] 1.326870e-104 2.653739e-104 1.0000000 [305,] 3.168018e-105 6.336036e-105 1.0000000 [306,] 6.864391e-106 1.372878e-105 1.0000000 [307,] 1.530165e-106 3.060329e-106 1.0000000 [308,] 5.105759e-107 1.021152e-106 1.0000000 [309,] 1.110077e-107 2.220154e-107 1.0000000 [310,] 2.585225e-108 5.170450e-108 1.0000000 [311,] 5.712446e-109 1.142489e-108 1.0000000 [312,] 1.305796e-109 2.611592e-109 1.0000000 [313,] 3.404426e-110 6.808853e-110 1.0000000 [314,] 7.619328e-111 1.523866e-110 1.0000000 [315,] 5.510041e-111 1.102008e-110 1.0000000 [316,] 2.035732e-111 4.071464e-111 1.0000000 [317,] 6.753344e-112 1.350669e-111 1.0000000 [318,] 1.943839e-112 3.887677e-112 1.0000000 [319,] 5.267180e-113 1.053436e-112 1.0000000 [320,] 1.485896e-113 2.971791e-113 1.0000000 [321,] 3.956625e-114 7.913249e-114 1.0000000 [322,] 9.733118e-115 1.946624e-114 1.0000000 [323,] 2.661099e-115 5.322198e-115 1.0000000 [324,] 1.021211e-115 2.042421e-115 1.0000000 [325,] 5.090742e-116 1.018148e-115 1.0000000 [326,] 3.014531e-105 6.029063e-105 1.0000000 [327,] 1.155867e-105 2.311734e-105 1.0000000 [328,] 3.098352e-106 6.196705e-106 1.0000000 [329,] 9.005273e-107 1.801055e-106 1.0000000 [330,] 1.244807e-101 2.489615e-101 1.0000000 [331,] 5.029316e-102 1.005863e-101 1.0000000 [332,] 1.781562e-102 3.563124e-102 1.0000000 [333,] 4.885771e-103 9.771542e-103 1.0000000 [334,] 1.676836e-103 3.353671e-103 1.0000000 [335,] 1.979255e-103 3.958509e-103 1.0000000 [336,] 5.201290e-104 1.040258e-103 1.0000000 [337,] 1.376615e-104 2.753231e-104 1.0000000 [338,] 3.533606e-105 7.067212e-105 1.0000000 [339,] 8.784442e-106 1.756888e-105 1.0000000 [340,] 2.107611e-106 4.215223e-106 1.0000000 [341,] 4.853327e-107 9.706654e-107 1.0000000 [342,] 1.048848e-107 2.097696e-107 1.0000000 [343,] 2.461267e-108 4.922534e-108 1.0000000 [344,] 5.471135e-109 1.094227e-108 1.0000000 [345,] 1.187433e-109 2.374867e-109 1.0000000 [346,] 2.647184e-110 5.294369e-110 1.0000000 [347,] 5.744695e-111 1.148939e-110 1.0000000 [348,] 1.430369e-111 2.860738e-111 1.0000000 [349,] 2.944446e-112 5.888891e-112 1.0000000 [350,] 7.082715e-113 1.416543e-112 1.0000000 [351,] 1.906257e-113 3.812513e-113 1.0000000 [352,] 5.196616e-114 1.039323e-113 1.0000000 [353,] 1.312205e-114 2.624410e-114 1.0000000 [354,] 4.503589e-115 9.007179e-115 1.0000000 [355,] 9.226647e-116 1.845329e-115 1.0000000 [356,] 1.197490e-115 2.394979e-115 1.0000000 [357,] 3.102670e-116 6.205341e-116 1.0000000 [358,] 7.052096e-117 1.410419e-116 1.0000000 [359,] 4.198098e-117 8.396196e-117 1.0000000 [360,] 9.636804e-118 1.927361e-117 1.0000000 [361,] 2.259706e-118 4.519412e-118 1.0000000 [362,] 6.009879e-119 1.201976e-118 1.0000000 [363,] 1.233548e-119 2.467096e-119 1.0000000 [364,] 2.426331e-120 4.852662e-120 1.0000000 [365,] 4.946111e-121 9.892222e-121 1.0000000 [366,] 1.466512e-121 2.933024e-121 1.0000000 [367,] 2.952689e-122 5.905378e-122 1.0000000 [368,] 5.814476e-123 1.162895e-122 1.0000000 [369,] 1.176756e-123 2.353512e-123 1.0000000 [370,] 2.697694e-124 5.395388e-124 1.0000000 [371,] 6.891738e-125 1.378348e-124 1.0000000 [372,] 1.573665e-125 3.147330e-125 1.0000000 [373,] 3.131195e-126 6.262391e-126 1.0000000 [374,] 6.141065e-127 1.228213e-126 1.0000000 [375,] 1.620770e-127 3.241540e-127 1.0000000 [376,] 3.276100e-128 6.552199e-128 1.0000000 [377,] 6.364333e-129 1.272867e-128 1.0000000 [378,] 1.301959e-129 2.603918e-129 1.0000000 [379,] 2.708485e-130 5.416971e-130 1.0000000 [380,] 5.699128e-131 1.139826e-130 1.0000000 [381,] 3.511269e-131 7.022539e-131 1.0000000 [382,] 3.531369e-131 7.062737e-131 1.0000000 [383,] 6.651369e-131 1.330274e-130 1.0000000 [384,] 1.726232e-130 3.452464e-130 1.0000000 [385,] 1.448708e-129 2.897416e-129 1.0000000 [386,] 3.602970e-128 7.205940e-128 1.0000000 [387,] 6.304723e-129 1.260945e-128 1.0000000 [388,] 1.484490e-129 2.968980e-129 1.0000000 [389,] 7.418507e-130 1.483701e-129 1.0000000 [390,] 1.493836e-130 2.987671e-130 1.0000000 [391,] 2.908137e-131 5.816275e-131 1.0000000 [392,] 5.379360e-132 1.075872e-131 1.0000000 [393,] 1.031742e-132 2.063485e-132 1.0000000 [394,] 1.944928e-133 3.889856e-133 1.0000000 [395,] 4.019090e-134 8.038180e-134 1.0000000 [396,] 6.615841e-135 1.323168e-134 1.0000000 [397,] 1.092723e-135 2.185447e-135 1.0000000 [398,] 2.088858e-136 4.177717e-136 1.0000000 [399,] 7.568946e-137 1.513789e-136 1.0000000 [400,] 1.191610e-137 2.383221e-137 1.0000000 [401,] 1.970007e-138 3.940014e-138 1.0000000 [402,] 4.146715e-139 8.293429e-139 1.0000000 [403,] 6.545276e-140 1.309055e-139 1.0000000 [404,] 1.022206e-140 2.044412e-140 1.0000000 [405,] 2.904400e-136 5.808800e-136 1.0000000 [406,] 2.620008e-134 5.240016e-134 1.0000000 [407,] 2.169570e-134 4.339141e-134 1.0000000 [408,] 2.169071e-133 4.338142e-133 1.0000000 [409,] 7.508239e-134 1.501648e-133 1.0000000 [410,] 3.247512e-134 6.495023e-134 1.0000000 [411,] 3.589991e-132 7.179981e-132 1.0000000 [412,] 1.222125e-132 2.444251e-132 1.0000000 [413,] 4.620918e-133 9.241837e-133 1.0000000 [414,] 7.126758e-134 1.425352e-133 1.0000000 [415,] 1.542844e-134 3.085688e-134 1.0000000 [416,] 2.304200e-135 4.608401e-135 1.0000000 [417,] 3.435922e-136 6.871845e-136 1.0000000 [418,] 5.094945e-137 1.018989e-136 1.0000000 [419,] 7.205805e-138 1.441161e-137 1.0000000 [420,] 1.682382e-138 3.364765e-138 1.0000000 [421,] 2.168200e-139 4.336399e-139 1.0000000 [422,] 6.613927e-140 1.322785e-139 1.0000000 [423,] 1.137715e-140 2.275429e-140 1.0000000 [424,] 1.638187e-141 3.276373e-141 1.0000000 [425,] 2.243482e-142 4.486964e-142 1.0000000 [426,] 3.010008e-143 6.020016e-143 1.0000000 [427,] 4.835170e-144 9.670341e-144 1.0000000 [428,] 5.599584e-145 1.119917e-144 1.0000000 [429,] 1.253184e-145 2.506367e-145 1.0000000 [430,] 1.379605e-146 2.759210e-146 1.0000000 [431,] 1.496795e-147 2.993590e-147 1.0000000 [432,] 2.313359e-148 4.626718e-148 1.0000000 [433,] 3.700213e-149 7.400426e-149 1.0000000 [434,] 4.850795e-150 9.701589e-150 1.0000000 [435,] 5.018896e-151 1.003779e-150 1.0000000 [436,] 5.552753e-152 1.110551e-151 1.0000000 [437,] 7.718970e-153 1.543794e-152 1.0000000 [438,] 1.194456e-153 2.388912e-153 1.0000000 [439,] 8.916069e-154 1.783214e-153 1.0000000 [440,] 5.896534e-87 1.179307e-86 1.0000000 [441,] 5.867151e-71 1.173430e-70 1.0000000 [442,] 8.311891e-66 1.662378e-65 1.0000000 [443,] 2.281689e-51 4.563378e-51 1.0000000 [444,] 9.220078e-47 1.844016e-46 1.0000000 [445,] 3.328407e-30 6.656813e-30 1.0000000 [446,] 7.430269e-31 1.486054e-30 1.0000000 [447,] 3.310870e-30 6.621741e-30 1.0000000 [448,] 1.615410e-25 3.230820e-25 1.0000000 [449,] 1.931648e-15 3.863296e-15 1.0000000 [450,] 6.503656e-13 1.300731e-12 1.0000000 [451,] 1.678937e-09 3.357873e-09 1.0000000 > postscript(file="/var/wessaorg/rcomp/tmp/1odwu1462484259.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/28dyn1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3gua71462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4yu8n1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/545l11462484259.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 = 462 Frequency = 1 1 2 3 4 5 0.865198442 0.575484035 1.706577971 0.663903979 1.175599512 6 7 8 9 10 2.348732313 0.861634159 0.788501358 1.651749637 -0.367271866 11 12 13 14 15 -0.472042462 -0.904600976 -0.686928535 -0.501410436 -0.843853472 16 17 18 19 20 -0.818107519 -0.855263412 -0.968739545 -1.242303828 -0.547499720 21 22 23 24 25 -0.846351146 -0.433908110 -0.645776859 -0.575922766 -0.274801521 26 27 28 29 30 0.169969075 -0.146554792 0.852466711 0.709595295 0.447152258 31 32 33 34 35 0.535398986 0.779337030 0.765945964 2.074709241 0.115399005 36 37 38 39 40 0.234997935 -0.339487068 -0.152589458 0.473703472 1.440400556 41 42 43 44 45 -0.209714922 -0.228107538 1.191491391 -0.534801521 -0.203163726 46 47 48 49 50 0.501120712 0.479798922 2.030430948 1.703047201 0.488507561 51 52 53 54 55 1.466295479 1.490689231 0.060084533 0.197298165 1.399890210 56 57 58 59 60 -0.848046698 -0.081437764 -0.767995143 -0.988888535 -1.222282702 61 62 63 64 65 -0.957396629 -1.650274248 -1.730803182 -0.782422425 -0.840158808 66 67 68 69 70 5.045769646 0.647121848 0.674250431 1.216292416 1.673217354 71 72 73 74 75 -0.654339610 0.374824718 0.030169601 0.260859365 0.478589545 76 77 78 79 80 0.785341248 1.126031012 0.693703453 0.831375895 0.764450957 81 82 83 84 85 0.071436754 -0.330948544 -0.405087113 0.822126518 0.069224672 86 87 88 89 90 0.226322827 -0.029137533 0.275459845 0.641953283 -0.386895023 91 92 93 94 95 -0.803877699 1.277817834 0.410145392 -0.195889255 0.029455628 96 97 98 99 100 0.227128069 0.063363242 0.061667709 0.262241996 -0.532644077 101 102 103 104 105 0.617355923 0.606322827 -0.074251461 0.110862467 -0.011580570 106 107 108 109 110 0.559452508 0.818820482 -0.609225683 -0.237329624 -0.077071341 111 112 113 114 115 -0.461209910 -0.638824612 -0.436211461 0.900312406 0.628501377 116 117 118 119 120 0.772755424 -0.393880763 -4.109082782 -2.315147840 -2.062008874 121 122 123 124 125 -0.773619416 0.288759642 0.507465179 0.927410542 -3.982504278 126 127 128 129 130 -0.492154838 -0.757615198 -0.826007815 -0.541179480 -0.498678705 131 132 133 134 135 -0.763449300 -0.705892337 -0.985433528 -0.150605193 1.028413246 136 137 138 139 140 -1.146588304 -0.218113722 -0.609320035 -0.627648729 -0.820982056 141 142 143 144 145 -0.586992476 -0.736305813 -1.504005563 -0.647788415 -0.691583671 146 147 148 149 150 1.017149195 0.172931761 -0.198590556 -0.400401566 -0.190401566 151 152 153 154 155 0.523387450 0.360889776 2.108042549 0.674134935 1.270859346 156 157 158 159 160 0.849163813 0.831059872 0.650427865 0.718100306 0.729795839 161 162 163 164 165 0.639106075 -0.057448222 -0.103169948 4.737030578 1.089042133 166 167 168 169 170 0.358668391 0.342712608 1.331549111 0.727006351 0.221114510 171 172 173 174 175 0.850291281 -0.890887704 0.578538009 -0.123273002 0.224168484 176 177 178 179 180 -0.041060920 0.044283962 0.113709675 -0.430544372 -7.911881256 181 182 183 184 185 -4.194727393 -3.044851648 -0.597296093 -5.976890982 0.046034132 186 187 188 189 190 -0.220173731 -0.177156408 0.561205798 0.533648835 0.516091871 191 192 193 194 195 0.153132287 -0.042528599 -0.370201041 1.086781617 0.032041451 196 197 198 199 200 0.402041451 1.189944848 -0.082355402 1.168218885 1.289136504 201 202 203 204 205 1.370750071 0.524457159 -0.697876564 -1.150662932 -2.918977229 206 207 208 209 210 -0.316527464 -0.175861926 -0.604254543 -0.608566329 0.005860935 211 212 213 214 215 0.271524922 -0.894026689 -1.060751101 -0.158396232 0.332898230 216 217 218 219 220 0.094277759 0.187237344 -0.262306948 -0.743343127 -0.610526348 221 222 223 224 225 1.259510265 -0.310489735 -0.674974737 0.123992166 -0.193163726 226 227 228 229 230 -0.371841936 0.346951751 -0.370924317 -0.329286523 0.202038369 231 232 233 234 235 -0.758535918 -0.654886569 -0.230088664 -0.222416223 0.340285078 236 237 238 239 240 0.946377464 -0.235375808 0.094566454 -0.204339610 -0.987846153 241 242 243 244 245 -1.005779961 -0.644427759 0.080516052 -0.676697579 -0.439140616 246 247 248 249 250 -0.509772642 -0.250404668 0.567468281 -0.025549043 1.627526019 251 252 253 254 255 0.814450957 0.511433633 0.476836255 1.202439402 0.261433633 256 257 258 259 260 0.545572203 -0.148800404 -0.068481299 0.102296634 -0.108362702 261 262 263 264 265 0.124770100 -0.785172162 -1.119459721 -0.487992042 -0.324023588 266 267 268 269 270 0.402734298 0.693682328 0.730060306 1.093019891 0.525979476 271 272 273 274 275 0.746611502 1.335833588 0.633420962 0.282296615 -0.069453537 276 277 278 279 280 -0.465804188 -0.458131746 -0.201033592 -0.129283422 0.260862467 281 282 283 284 285 0.976322827 -0.121781096 3.639336954 2.730026757 1.110285022 286 287 288 289 290 8.898701865 2.696350079 2.519020970 1.968392064 5.838793135 291 292 293 294 295 1.471467126 1.599598377 0.659880906 -0.508973621 1.700828936 296 297 298 299 300 -0.043883921 -0.150462425 0.403013708 0.850081432 0.554736550 301 302 303 304 305 0.408759642 0.781290846 0.628331262 0.161549111 1.076893993 306 307 308 309 310 0.567583758 0.665198461 1.343244644 0.865687681 0.824049886 311 312 313 314 315 -0.245002046 -0.572674488 -1.285779961 -0.363510141 0.069194262 316 317 318 319 320 -0.461322286 0.143390570 0.236751225 -0.302589439 0.027650782 321 322 323 324 325 0.688656550 1.870467561 1.626098036 1.138656550 1.407277021 326 327 328 329 330 1.201327441 0.854138036 1.004229286 0.181871317 0.158449822 331 332 333 334 335 6.465742318 0.224766960 0.565572203 0.708735415 5.305660352 336 337 338 339 340 0.557355885 1.494766942 0.500692332 -0.127700284 1.860892877 341 342 343 344 345 0.471837805 0.777410542 0.292928641 0.480169601 0.323761211 346 347 348 349 350 0.165405208 -0.344257644 -0.750061336 -0.453938539 -0.097186818 351 352 353 354 355 0.048158064 -0.431267649 0.112323962 -0.432215678 -1.207019785 356 357 358 359 360 0.281351705 -0.926262997 0.072843611 0.424770100 -0.391492402 361 362 363 364 365 1.003648854 -0.107417755 -1.273829245 -3.739044253 0.274800510 366 367 368 369 370 -0.525600560 0.420090755 -0.011951211 -0.304336509 0.063998369 371 372 373 374 375 0.785119615 -0.073674072 -0.142984307 -0.260431996 -0.271927003 376 377 378 379 380 0.556492942 0.312585328 -0.218104437 0.021895563 0.527182707 381 382 383 384 385 0.164165383 -0.008162176 -0.756089780 -0.815804188 -1.762544068 386 387 388 389 390 -4.429099436 -4.913940156 -5.396902842 -5.620950725 -6.386280665 391 392 393 394 395 -6.022559218 -0.035776878 -0.491753786 1.136894012 0.673217335 396 397 398 399 400 -0.082674506 -0.004604096 0.350543343 0.221175369 0.541375895 401 402 403 404 405 -0.327183717 -0.002413122 -0.729338059 0.773047238 -0.174567464 406 407 408 409 410 -0.382586338 0.402816283 -0.387125978 -0.160316518 -10.049718136 411 412 413 414 415 -7.013190096 -1.991177470 -5.492387410 0.189531410 -2.757390972 416 417 418 419 420 -6.398519491 -2.173103413 -1.902771922 -0.411322286 -0.915403117 421 422 423 424 425 -0.124828830 -0.440517044 -0.433303412 -0.235229900 0.745833607 426 427 428 429 430 0.176894012 -1.661578014 0.320570652 0.656979042 0.746805825 431 432 433 434 435 1.356979042 0.379996365 0.921318156 1.589738101 0.715082983 436 437 438 439 440 0.341117630 -0.533221465 -0.570435097 0.528215803 0.023560685 441 442 443 444 445 -0.263364252 -0.475634072 -0.122732226 -0.485807289 -0.708134848 446 447 448 449 450 9.680386807 5.239851784 1.873762631 -9.108920983 -3.586893019 451 452 453 454 455 -14.494274829 -12.782180687 -10.891846677 -1.722907048 0.787026584 456 457 458 459 460 8.646975723 6.299573498 1.029200357 16.526065883 0.902398981 461 462 -2.859102266 10.958188371 > postscript(file="/var/wessaorg/rcomp/tmp/6yert1462484259.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 = 462 Frequency = 1 lag(myerror, k = 1) myerror 0 0.865198442 NA 1 0.575484035 0.865198442 2 1.706577971 0.575484035 3 0.663903979 1.706577971 4 1.175599512 0.663903979 5 2.348732313 1.175599512 6 0.861634159 2.348732313 7 0.788501358 0.861634159 8 1.651749637 0.788501358 9 -0.367271866 1.651749637 10 -0.472042462 -0.367271866 11 -0.904600976 -0.472042462 12 -0.686928535 -0.904600976 13 -0.501410436 -0.686928535 14 -0.843853472 -0.501410436 15 -0.818107519 -0.843853472 16 -0.855263412 -0.818107519 17 -0.968739545 -0.855263412 18 -1.242303828 -0.968739545 19 -0.547499720 -1.242303828 20 -0.846351146 -0.547499720 21 -0.433908110 -0.846351146 22 -0.645776859 -0.433908110 23 -0.575922766 -0.645776859 24 -0.274801521 -0.575922766 25 0.169969075 -0.274801521 26 -0.146554792 0.169969075 27 0.852466711 -0.146554792 28 0.709595295 0.852466711 29 0.447152258 0.709595295 30 0.535398986 0.447152258 31 0.779337030 0.535398986 32 0.765945964 0.779337030 33 2.074709241 0.765945964 34 0.115399005 2.074709241 35 0.234997935 0.115399005 36 -0.339487068 0.234997935 37 -0.152589458 -0.339487068 38 0.473703472 -0.152589458 39 1.440400556 0.473703472 40 -0.209714922 1.440400556 41 -0.228107538 -0.209714922 42 1.191491391 -0.228107538 43 -0.534801521 1.191491391 44 -0.203163726 -0.534801521 45 0.501120712 -0.203163726 46 0.479798922 0.501120712 47 2.030430948 0.479798922 48 1.703047201 2.030430948 49 0.488507561 1.703047201 50 1.466295479 0.488507561 51 1.490689231 1.466295479 52 0.060084533 1.490689231 53 0.197298165 0.060084533 54 1.399890210 0.197298165 55 -0.848046698 1.399890210 56 -0.081437764 -0.848046698 57 -0.767995143 -0.081437764 58 -0.988888535 -0.767995143 59 -1.222282702 -0.988888535 60 -0.957396629 -1.222282702 61 -1.650274248 -0.957396629 62 -1.730803182 -1.650274248 63 -0.782422425 -1.730803182 64 -0.840158808 -0.782422425 65 5.045769646 -0.840158808 66 0.647121848 5.045769646 67 0.674250431 0.647121848 68 1.216292416 0.674250431 69 1.673217354 1.216292416 70 -0.654339610 1.673217354 71 0.374824718 -0.654339610 72 0.030169601 0.374824718 73 0.260859365 0.030169601 74 0.478589545 0.260859365 75 0.785341248 0.478589545 76 1.126031012 0.785341248 77 0.693703453 1.126031012 78 0.831375895 0.693703453 79 0.764450957 0.831375895 80 0.071436754 0.764450957 81 -0.330948544 0.071436754 82 -0.405087113 -0.330948544 83 0.822126518 -0.405087113 84 0.069224672 0.822126518 85 0.226322827 0.069224672 86 -0.029137533 0.226322827 87 0.275459845 -0.029137533 88 0.641953283 0.275459845 89 -0.386895023 0.641953283 90 -0.803877699 -0.386895023 91 1.277817834 -0.803877699 92 0.410145392 1.277817834 93 -0.195889255 0.410145392 94 0.029455628 -0.195889255 95 0.227128069 0.029455628 96 0.063363242 0.227128069 97 0.061667709 0.063363242 98 0.262241996 0.061667709 99 -0.532644077 0.262241996 100 0.617355923 -0.532644077 101 0.606322827 0.617355923 102 -0.074251461 0.606322827 103 0.110862467 -0.074251461 104 -0.011580570 0.110862467 105 0.559452508 -0.011580570 106 0.818820482 0.559452508 107 -0.609225683 0.818820482 108 -0.237329624 -0.609225683 109 -0.077071341 -0.237329624 110 -0.461209910 -0.077071341 111 -0.638824612 -0.461209910 112 -0.436211461 -0.638824612 113 0.900312406 -0.436211461 114 0.628501377 0.900312406 115 0.772755424 0.628501377 116 -0.393880763 0.772755424 117 -4.109082782 -0.393880763 118 -2.315147840 -4.109082782 119 -2.062008874 -2.315147840 120 -0.773619416 -2.062008874 121 0.288759642 -0.773619416 122 0.507465179 0.288759642 123 0.927410542 0.507465179 124 -3.982504278 0.927410542 125 -0.492154838 -3.982504278 126 -0.757615198 -0.492154838 127 -0.826007815 -0.757615198 128 -0.541179480 -0.826007815 129 -0.498678705 -0.541179480 130 -0.763449300 -0.498678705 131 -0.705892337 -0.763449300 132 -0.985433528 -0.705892337 133 -0.150605193 -0.985433528 134 1.028413246 -0.150605193 135 -1.146588304 1.028413246 136 -0.218113722 -1.146588304 137 -0.609320035 -0.218113722 138 -0.627648729 -0.609320035 139 -0.820982056 -0.627648729 140 -0.586992476 -0.820982056 141 -0.736305813 -0.586992476 142 -1.504005563 -0.736305813 143 -0.647788415 -1.504005563 144 -0.691583671 -0.647788415 145 1.017149195 -0.691583671 146 0.172931761 1.017149195 147 -0.198590556 0.172931761 148 -0.400401566 -0.198590556 149 -0.190401566 -0.400401566 150 0.523387450 -0.190401566 151 0.360889776 0.523387450 152 2.108042549 0.360889776 153 0.674134935 2.108042549 154 1.270859346 0.674134935 155 0.849163813 1.270859346 156 0.831059872 0.849163813 157 0.650427865 0.831059872 158 0.718100306 0.650427865 159 0.729795839 0.718100306 160 0.639106075 0.729795839 161 -0.057448222 0.639106075 162 -0.103169948 -0.057448222 163 4.737030578 -0.103169948 164 1.089042133 4.737030578 165 0.358668391 1.089042133 166 0.342712608 0.358668391 167 1.331549111 0.342712608 168 0.727006351 1.331549111 169 0.221114510 0.727006351 170 0.850291281 0.221114510 171 -0.890887704 0.850291281 172 0.578538009 -0.890887704 173 -0.123273002 0.578538009 174 0.224168484 -0.123273002 175 -0.041060920 0.224168484 176 0.044283962 -0.041060920 177 0.113709675 0.044283962 178 -0.430544372 0.113709675 179 -7.911881256 -0.430544372 180 -4.194727393 -7.911881256 181 -3.044851648 -4.194727393 182 -0.597296093 -3.044851648 183 -5.976890982 -0.597296093 184 0.046034132 -5.976890982 185 -0.220173731 0.046034132 186 -0.177156408 -0.220173731 187 0.561205798 -0.177156408 188 0.533648835 0.561205798 189 0.516091871 0.533648835 190 0.153132287 0.516091871 191 -0.042528599 0.153132287 192 -0.370201041 -0.042528599 193 1.086781617 -0.370201041 194 0.032041451 1.086781617 195 0.402041451 0.032041451 196 1.189944848 0.402041451 197 -0.082355402 1.189944848 198 1.168218885 -0.082355402 199 1.289136504 1.168218885 200 1.370750071 1.289136504 201 0.524457159 1.370750071 202 -0.697876564 0.524457159 203 -1.150662932 -0.697876564 204 -2.918977229 -1.150662932 205 -0.316527464 -2.918977229 206 -0.175861926 -0.316527464 207 -0.604254543 -0.175861926 208 -0.608566329 -0.604254543 209 0.005860935 -0.608566329 210 0.271524922 0.005860935 211 -0.894026689 0.271524922 212 -1.060751101 -0.894026689 213 -0.158396232 -1.060751101 214 0.332898230 -0.158396232 215 0.094277759 0.332898230 216 0.187237344 0.094277759 217 -0.262306948 0.187237344 218 -0.743343127 -0.262306948 219 -0.610526348 -0.743343127 220 1.259510265 -0.610526348 221 -0.310489735 1.259510265 222 -0.674974737 -0.310489735 223 0.123992166 -0.674974737 224 -0.193163726 0.123992166 225 -0.371841936 -0.193163726 226 0.346951751 -0.371841936 227 -0.370924317 0.346951751 228 -0.329286523 -0.370924317 229 0.202038369 -0.329286523 230 -0.758535918 0.202038369 231 -0.654886569 -0.758535918 232 -0.230088664 -0.654886569 233 -0.222416223 -0.230088664 234 0.340285078 -0.222416223 235 0.946377464 0.340285078 236 -0.235375808 0.946377464 237 0.094566454 -0.235375808 238 -0.204339610 0.094566454 239 -0.987846153 -0.204339610 240 -1.005779961 -0.987846153 241 -0.644427759 -1.005779961 242 0.080516052 -0.644427759 243 -0.676697579 0.080516052 244 -0.439140616 -0.676697579 245 -0.509772642 -0.439140616 246 -0.250404668 -0.509772642 247 0.567468281 -0.250404668 248 -0.025549043 0.567468281 249 1.627526019 -0.025549043 250 0.814450957 1.627526019 251 0.511433633 0.814450957 252 0.476836255 0.511433633 253 1.202439402 0.476836255 254 0.261433633 1.202439402 255 0.545572203 0.261433633 256 -0.148800404 0.545572203 257 -0.068481299 -0.148800404 258 0.102296634 -0.068481299 259 -0.108362702 0.102296634 260 0.124770100 -0.108362702 261 -0.785172162 0.124770100 262 -1.119459721 -0.785172162 263 -0.487992042 -1.119459721 264 -0.324023588 -0.487992042 265 0.402734298 -0.324023588 266 0.693682328 0.402734298 267 0.730060306 0.693682328 268 1.093019891 0.730060306 269 0.525979476 1.093019891 270 0.746611502 0.525979476 271 1.335833588 0.746611502 272 0.633420962 1.335833588 273 0.282296615 0.633420962 274 -0.069453537 0.282296615 275 -0.465804188 -0.069453537 276 -0.458131746 -0.465804188 277 -0.201033592 -0.458131746 278 -0.129283422 -0.201033592 279 0.260862467 -0.129283422 280 0.976322827 0.260862467 281 -0.121781096 0.976322827 282 3.639336954 -0.121781096 283 2.730026757 3.639336954 284 1.110285022 2.730026757 285 8.898701865 1.110285022 286 2.696350079 8.898701865 287 2.519020970 2.696350079 288 1.968392064 2.519020970 289 5.838793135 1.968392064 290 1.471467126 5.838793135 291 1.599598377 1.471467126 292 0.659880906 1.599598377 293 -0.508973621 0.659880906 294 1.700828936 -0.508973621 295 -0.043883921 1.700828936 296 -0.150462425 -0.043883921 297 0.403013708 -0.150462425 298 0.850081432 0.403013708 299 0.554736550 0.850081432 300 0.408759642 0.554736550 301 0.781290846 0.408759642 302 0.628331262 0.781290846 303 0.161549111 0.628331262 304 1.076893993 0.161549111 305 0.567583758 1.076893993 306 0.665198461 0.567583758 307 1.343244644 0.665198461 308 0.865687681 1.343244644 309 0.824049886 0.865687681 310 -0.245002046 0.824049886 311 -0.572674488 -0.245002046 312 -1.285779961 -0.572674488 313 -0.363510141 -1.285779961 314 0.069194262 -0.363510141 315 -0.461322286 0.069194262 316 0.143390570 -0.461322286 317 0.236751225 0.143390570 318 -0.302589439 0.236751225 319 0.027650782 -0.302589439 320 0.688656550 0.027650782 321 1.870467561 0.688656550 322 1.626098036 1.870467561 323 1.138656550 1.626098036 324 1.407277021 1.138656550 325 1.201327441 1.407277021 326 0.854138036 1.201327441 327 1.004229286 0.854138036 328 0.181871317 1.004229286 329 0.158449822 0.181871317 330 6.465742318 0.158449822 331 0.224766960 6.465742318 332 0.565572203 0.224766960 333 0.708735415 0.565572203 334 5.305660352 0.708735415 335 0.557355885 5.305660352 336 1.494766942 0.557355885 337 0.500692332 1.494766942 338 -0.127700284 0.500692332 339 1.860892877 -0.127700284 340 0.471837805 1.860892877 341 0.777410542 0.471837805 342 0.292928641 0.777410542 343 0.480169601 0.292928641 344 0.323761211 0.480169601 345 0.165405208 0.323761211 346 -0.344257644 0.165405208 347 -0.750061336 -0.344257644 348 -0.453938539 -0.750061336 349 -0.097186818 -0.453938539 350 0.048158064 -0.097186818 351 -0.431267649 0.048158064 352 0.112323962 -0.431267649 353 -0.432215678 0.112323962 354 -1.207019785 -0.432215678 355 0.281351705 -1.207019785 356 -0.926262997 0.281351705 357 0.072843611 -0.926262997 358 0.424770100 0.072843611 359 -0.391492402 0.424770100 360 1.003648854 -0.391492402 361 -0.107417755 1.003648854 362 -1.273829245 -0.107417755 363 -3.739044253 -1.273829245 364 0.274800510 -3.739044253 365 -0.525600560 0.274800510 366 0.420090755 -0.525600560 367 -0.011951211 0.420090755 368 -0.304336509 -0.011951211 369 0.063998369 -0.304336509 370 0.785119615 0.063998369 371 -0.073674072 0.785119615 372 -0.142984307 -0.073674072 373 -0.260431996 -0.142984307 374 -0.271927003 -0.260431996 375 0.556492942 -0.271927003 376 0.312585328 0.556492942 377 -0.218104437 0.312585328 378 0.021895563 -0.218104437 379 0.527182707 0.021895563 380 0.164165383 0.527182707 381 -0.008162176 0.164165383 382 -0.756089780 -0.008162176 383 -0.815804188 -0.756089780 384 -1.762544068 -0.815804188 385 -4.429099436 -1.762544068 386 -4.913940156 -4.429099436 387 -5.396902842 -4.913940156 388 -5.620950725 -5.396902842 389 -6.386280665 -5.620950725 390 -6.022559218 -6.386280665 391 -0.035776878 -6.022559218 392 -0.491753786 -0.035776878 393 1.136894012 -0.491753786 394 0.673217335 1.136894012 395 -0.082674506 0.673217335 396 -0.004604096 -0.082674506 397 0.350543343 -0.004604096 398 0.221175369 0.350543343 399 0.541375895 0.221175369 400 -0.327183717 0.541375895 401 -0.002413122 -0.327183717 402 -0.729338059 -0.002413122 403 0.773047238 -0.729338059 404 -0.174567464 0.773047238 405 -0.382586338 -0.174567464 406 0.402816283 -0.382586338 407 -0.387125978 0.402816283 408 -0.160316518 -0.387125978 409 -10.049718136 -0.160316518 410 -7.013190096 -10.049718136 411 -1.991177470 -7.013190096 412 -5.492387410 -1.991177470 413 0.189531410 -5.492387410 414 -2.757390972 0.189531410 415 -6.398519491 -2.757390972 416 -2.173103413 -6.398519491 417 -1.902771922 -2.173103413 418 -0.411322286 -1.902771922 419 -0.915403117 -0.411322286 420 -0.124828830 -0.915403117 421 -0.440517044 -0.124828830 422 -0.433303412 -0.440517044 423 -0.235229900 -0.433303412 424 0.745833607 -0.235229900 425 0.176894012 0.745833607 426 -1.661578014 0.176894012 427 0.320570652 -1.661578014 428 0.656979042 0.320570652 429 0.746805825 0.656979042 430 1.356979042 0.746805825 431 0.379996365 1.356979042 432 0.921318156 0.379996365 433 1.589738101 0.921318156 434 0.715082983 1.589738101 435 0.341117630 0.715082983 436 -0.533221465 0.341117630 437 -0.570435097 -0.533221465 438 0.528215803 -0.570435097 439 0.023560685 0.528215803 440 -0.263364252 0.023560685 441 -0.475634072 -0.263364252 442 -0.122732226 -0.475634072 443 -0.485807289 -0.122732226 444 -0.708134848 -0.485807289 445 9.680386807 -0.708134848 446 5.239851784 9.680386807 447 1.873762631 5.239851784 448 -9.108920983 1.873762631 449 -3.586893019 -9.108920983 450 -14.494274829 -3.586893019 451 -12.782180687 -14.494274829 452 -10.891846677 -12.782180687 453 -1.722907048 -10.891846677 454 0.787026584 -1.722907048 455 8.646975723 0.787026584 456 6.299573498 8.646975723 457 1.029200357 6.299573498 458 16.526065883 1.029200357 459 0.902398981 16.526065883 460 -2.859102266 0.902398981 461 10.958188371 -2.859102266 462 NA 10.958188371 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.575484035 0.865198442 [2,] 1.706577971 0.575484035 [3,] 0.663903979 1.706577971 [4,] 1.175599512 0.663903979 [5,] 2.348732313 1.175599512 [6,] 0.861634159 2.348732313 [7,] 0.788501358 0.861634159 [8,] 1.651749637 0.788501358 [9,] -0.367271866 1.651749637 [10,] -0.472042462 -0.367271866 [11,] -0.904600976 -0.472042462 [12,] -0.686928535 -0.904600976 [13,] -0.501410436 -0.686928535 [14,] -0.843853472 -0.501410436 [15,] -0.818107519 -0.843853472 [16,] -0.855263412 -0.818107519 [17,] -0.968739545 -0.855263412 [18,] -1.242303828 -0.968739545 [19,] -0.547499720 -1.242303828 [20,] -0.846351146 -0.547499720 [21,] -0.433908110 -0.846351146 [22,] -0.645776859 -0.433908110 [23,] -0.575922766 -0.645776859 [24,] -0.274801521 -0.575922766 [25,] 0.169969075 -0.274801521 [26,] -0.146554792 0.169969075 [27,] 0.852466711 -0.146554792 [28,] 0.709595295 0.852466711 [29,] 0.447152258 0.709595295 [30,] 0.535398986 0.447152258 [31,] 0.779337030 0.535398986 [32,] 0.765945964 0.779337030 [33,] 2.074709241 0.765945964 [34,] 0.115399005 2.074709241 [35,] 0.234997935 0.115399005 [36,] -0.339487068 0.234997935 [37,] -0.152589458 -0.339487068 [38,] 0.473703472 -0.152589458 [39,] 1.440400556 0.473703472 [40,] -0.209714922 1.440400556 [41,] -0.228107538 -0.209714922 [42,] 1.191491391 -0.228107538 [43,] -0.534801521 1.191491391 [44,] -0.203163726 -0.534801521 [45,] 0.501120712 -0.203163726 [46,] 0.479798922 0.501120712 [47,] 2.030430948 0.479798922 [48,] 1.703047201 2.030430948 [49,] 0.488507561 1.703047201 [50,] 1.466295479 0.488507561 [51,] 1.490689231 1.466295479 [52,] 0.060084533 1.490689231 [53,] 0.197298165 0.060084533 [54,] 1.399890210 0.197298165 [55,] -0.848046698 1.399890210 [56,] -0.081437764 -0.848046698 [57,] -0.767995143 -0.081437764 [58,] -0.988888535 -0.767995143 [59,] -1.222282702 -0.988888535 [60,] -0.957396629 -1.222282702 [61,] -1.650274248 -0.957396629 [62,] -1.730803182 -1.650274248 [63,] -0.782422425 -1.730803182 [64,] -0.840158808 -0.782422425 [65,] 5.045769646 -0.840158808 [66,] 0.647121848 5.045769646 [67,] 0.674250431 0.647121848 [68,] 1.216292416 0.674250431 [69,] 1.673217354 1.216292416 [70,] -0.654339610 1.673217354 [71,] 0.374824718 -0.654339610 [72,] 0.030169601 0.374824718 [73,] 0.260859365 0.030169601 [74,] 0.478589545 0.260859365 [75,] 0.785341248 0.478589545 [76,] 1.126031012 0.785341248 [77,] 0.693703453 1.126031012 [78,] 0.831375895 0.693703453 [79,] 0.764450957 0.831375895 [80,] 0.071436754 0.764450957 [81,] -0.330948544 0.071436754 [82,] -0.405087113 -0.330948544 [83,] 0.822126518 -0.405087113 [84,] 0.069224672 0.822126518 [85,] 0.226322827 0.069224672 [86,] -0.029137533 0.226322827 [87,] 0.275459845 -0.029137533 [88,] 0.641953283 0.275459845 [89,] -0.386895023 0.641953283 [90,] -0.803877699 -0.386895023 [91,] 1.277817834 -0.803877699 [92,] 0.410145392 1.277817834 [93,] -0.195889255 0.410145392 [94,] 0.029455628 -0.195889255 [95,] 0.227128069 0.029455628 [96,] 0.063363242 0.227128069 [97,] 0.061667709 0.063363242 [98,] 0.262241996 0.061667709 [99,] -0.532644077 0.262241996 [100,] 0.617355923 -0.532644077 [101,] 0.606322827 0.617355923 [102,] -0.074251461 0.606322827 [103,] 0.110862467 -0.074251461 [104,] -0.011580570 0.110862467 [105,] 0.559452508 -0.011580570 [106,] 0.818820482 0.559452508 [107,] -0.609225683 0.818820482 [108,] -0.237329624 -0.609225683 [109,] -0.077071341 -0.237329624 [110,] -0.461209910 -0.077071341 [111,] -0.638824612 -0.461209910 [112,] -0.436211461 -0.638824612 [113,] 0.900312406 -0.436211461 [114,] 0.628501377 0.900312406 [115,] 0.772755424 0.628501377 [116,] -0.393880763 0.772755424 [117,] -4.109082782 -0.393880763 [118,] -2.315147840 -4.109082782 [119,] -2.062008874 -2.315147840 [120,] -0.773619416 -2.062008874 [121,] 0.288759642 -0.773619416 [122,] 0.507465179 0.288759642 [123,] 0.927410542 0.507465179 [124,] -3.982504278 0.927410542 [125,] -0.492154838 -3.982504278 [126,] -0.757615198 -0.492154838 [127,] -0.826007815 -0.757615198 [128,] -0.541179480 -0.826007815 [129,] -0.498678705 -0.541179480 [130,] -0.763449300 -0.498678705 [131,] -0.705892337 -0.763449300 [132,] -0.985433528 -0.705892337 [133,] -0.150605193 -0.985433528 [134,] 1.028413246 -0.150605193 [135,] -1.146588304 1.028413246 [136,] -0.218113722 -1.146588304 [137,] -0.609320035 -0.218113722 [138,] -0.627648729 -0.609320035 [139,] -0.820982056 -0.627648729 [140,] -0.586992476 -0.820982056 [141,] -0.736305813 -0.586992476 [142,] -1.504005563 -0.736305813 [143,] -0.647788415 -1.504005563 [144,] -0.691583671 -0.647788415 [145,] 1.017149195 -0.691583671 [146,] 0.172931761 1.017149195 [147,] -0.198590556 0.172931761 [148,] -0.400401566 -0.198590556 [149,] -0.190401566 -0.400401566 [150,] 0.523387450 -0.190401566 [151,] 0.360889776 0.523387450 [152,] 2.108042549 0.360889776 [153,] 0.674134935 2.108042549 [154,] 1.270859346 0.674134935 [155,] 0.849163813 1.270859346 [156,] 0.831059872 0.849163813 [157,] 0.650427865 0.831059872 [158,] 0.718100306 0.650427865 [159,] 0.729795839 0.718100306 [160,] 0.639106075 0.729795839 [161,] -0.057448222 0.639106075 [162,] -0.103169948 -0.057448222 [163,] 4.737030578 -0.103169948 [164,] 1.089042133 4.737030578 [165,] 0.358668391 1.089042133 [166,] 0.342712608 0.358668391 [167,] 1.331549111 0.342712608 [168,] 0.727006351 1.331549111 [169,] 0.221114510 0.727006351 [170,] 0.850291281 0.221114510 [171,] -0.890887704 0.850291281 [172,] 0.578538009 -0.890887704 [173,] -0.123273002 0.578538009 [174,] 0.224168484 -0.123273002 [175,] -0.041060920 0.224168484 [176,] 0.044283962 -0.041060920 [177,] 0.113709675 0.044283962 [178,] -0.430544372 0.113709675 [179,] -7.911881256 -0.430544372 [180,] -4.194727393 -7.911881256 [181,] -3.044851648 -4.194727393 [182,] -0.597296093 -3.044851648 [183,] -5.976890982 -0.597296093 [184,] 0.046034132 -5.976890982 [185,] -0.220173731 0.046034132 [186,] -0.177156408 -0.220173731 [187,] 0.561205798 -0.177156408 [188,] 0.533648835 0.561205798 [189,] 0.516091871 0.533648835 [190,] 0.153132287 0.516091871 [191,] -0.042528599 0.153132287 [192,] -0.370201041 -0.042528599 [193,] 1.086781617 -0.370201041 [194,] 0.032041451 1.086781617 [195,] 0.402041451 0.032041451 [196,] 1.189944848 0.402041451 [197,] -0.082355402 1.189944848 [198,] 1.168218885 -0.082355402 [199,] 1.289136504 1.168218885 [200,] 1.370750071 1.289136504 [201,] 0.524457159 1.370750071 [202,] -0.697876564 0.524457159 [203,] -1.150662932 -0.697876564 [204,] -2.918977229 -1.150662932 [205,] -0.316527464 -2.918977229 [206,] -0.175861926 -0.316527464 [207,] -0.604254543 -0.175861926 [208,] -0.608566329 -0.604254543 [209,] 0.005860935 -0.608566329 [210,] 0.271524922 0.005860935 [211,] -0.894026689 0.271524922 [212,] -1.060751101 -0.894026689 [213,] -0.158396232 -1.060751101 [214,] 0.332898230 -0.158396232 [215,] 0.094277759 0.332898230 [216,] 0.187237344 0.094277759 [217,] -0.262306948 0.187237344 [218,] -0.743343127 -0.262306948 [219,] -0.610526348 -0.743343127 [220,] 1.259510265 -0.610526348 [221,] -0.310489735 1.259510265 [222,] -0.674974737 -0.310489735 [223,] 0.123992166 -0.674974737 [224,] -0.193163726 0.123992166 [225,] -0.371841936 -0.193163726 [226,] 0.346951751 -0.371841936 [227,] -0.370924317 0.346951751 [228,] -0.329286523 -0.370924317 [229,] 0.202038369 -0.329286523 [230,] -0.758535918 0.202038369 [231,] -0.654886569 -0.758535918 [232,] -0.230088664 -0.654886569 [233,] -0.222416223 -0.230088664 [234,] 0.340285078 -0.222416223 [235,] 0.946377464 0.340285078 [236,] -0.235375808 0.946377464 [237,] 0.094566454 -0.235375808 [238,] -0.204339610 0.094566454 [239,] -0.987846153 -0.204339610 [240,] -1.005779961 -0.987846153 [241,] -0.644427759 -1.005779961 [242,] 0.080516052 -0.644427759 [243,] -0.676697579 0.080516052 [244,] -0.439140616 -0.676697579 [245,] -0.509772642 -0.439140616 [246,] -0.250404668 -0.509772642 [247,] 0.567468281 -0.250404668 [248,] -0.025549043 0.567468281 [249,] 1.627526019 -0.025549043 [250,] 0.814450957 1.627526019 [251,] 0.511433633 0.814450957 [252,] 0.476836255 0.511433633 [253,] 1.202439402 0.476836255 [254,] 0.261433633 1.202439402 [255,] 0.545572203 0.261433633 [256,] -0.148800404 0.545572203 [257,] -0.068481299 -0.148800404 [258,] 0.102296634 -0.068481299 [259,] -0.108362702 0.102296634 [260,] 0.124770100 -0.108362702 [261,] -0.785172162 0.124770100 [262,] -1.119459721 -0.785172162 [263,] -0.487992042 -1.119459721 [264,] -0.324023588 -0.487992042 [265,] 0.402734298 -0.324023588 [266,] 0.693682328 0.402734298 [267,] 0.730060306 0.693682328 [268,] 1.093019891 0.730060306 [269,] 0.525979476 1.093019891 [270,] 0.746611502 0.525979476 [271,] 1.335833588 0.746611502 [272,] 0.633420962 1.335833588 [273,] 0.282296615 0.633420962 [274,] -0.069453537 0.282296615 [275,] -0.465804188 -0.069453537 [276,] -0.458131746 -0.465804188 [277,] -0.201033592 -0.458131746 [278,] -0.129283422 -0.201033592 [279,] 0.260862467 -0.129283422 [280,] 0.976322827 0.260862467 [281,] -0.121781096 0.976322827 [282,] 3.639336954 -0.121781096 [283,] 2.730026757 3.639336954 [284,] 1.110285022 2.730026757 [285,] 8.898701865 1.110285022 [286,] 2.696350079 8.898701865 [287,] 2.519020970 2.696350079 [288,] 1.968392064 2.519020970 [289,] 5.838793135 1.968392064 [290,] 1.471467126 5.838793135 [291,] 1.599598377 1.471467126 [292,] 0.659880906 1.599598377 [293,] -0.508973621 0.659880906 [294,] 1.700828936 -0.508973621 [295,] -0.043883921 1.700828936 [296,] -0.150462425 -0.043883921 [297,] 0.403013708 -0.150462425 [298,] 0.850081432 0.403013708 [299,] 0.554736550 0.850081432 [300,] 0.408759642 0.554736550 [301,] 0.781290846 0.408759642 [302,] 0.628331262 0.781290846 [303,] 0.161549111 0.628331262 [304,] 1.076893993 0.161549111 [305,] 0.567583758 1.076893993 [306,] 0.665198461 0.567583758 [307,] 1.343244644 0.665198461 [308,] 0.865687681 1.343244644 [309,] 0.824049886 0.865687681 [310,] -0.245002046 0.824049886 [311,] -0.572674488 -0.245002046 [312,] -1.285779961 -0.572674488 [313,] -0.363510141 -1.285779961 [314,] 0.069194262 -0.363510141 [315,] -0.461322286 0.069194262 [316,] 0.143390570 -0.461322286 [317,] 0.236751225 0.143390570 [318,] -0.302589439 0.236751225 [319,] 0.027650782 -0.302589439 [320,] 0.688656550 0.027650782 [321,] 1.870467561 0.688656550 [322,] 1.626098036 1.870467561 [323,] 1.138656550 1.626098036 [324,] 1.407277021 1.138656550 [325,] 1.201327441 1.407277021 [326,] 0.854138036 1.201327441 [327,] 1.004229286 0.854138036 [328,] 0.181871317 1.004229286 [329,] 0.158449822 0.181871317 [330,] 6.465742318 0.158449822 [331,] 0.224766960 6.465742318 [332,] 0.565572203 0.224766960 [333,] 0.708735415 0.565572203 [334,] 5.305660352 0.708735415 [335,] 0.557355885 5.305660352 [336,] 1.494766942 0.557355885 [337,] 0.500692332 1.494766942 [338,] -0.127700284 0.500692332 [339,] 1.860892877 -0.127700284 [340,] 0.471837805 1.860892877 [341,] 0.777410542 0.471837805 [342,] 0.292928641 0.777410542 [343,] 0.480169601 0.292928641 [344,] 0.323761211 0.480169601 [345,] 0.165405208 0.323761211 [346,] -0.344257644 0.165405208 [347,] -0.750061336 -0.344257644 [348,] -0.453938539 -0.750061336 [349,] -0.097186818 -0.453938539 [350,] 0.048158064 -0.097186818 [351,] -0.431267649 0.048158064 [352,] 0.112323962 -0.431267649 [353,] -0.432215678 0.112323962 [354,] -1.207019785 -0.432215678 [355,] 0.281351705 -1.207019785 [356,] -0.926262997 0.281351705 [357,] 0.072843611 -0.926262997 [358,] 0.424770100 0.072843611 [359,] -0.391492402 0.424770100 [360,] 1.003648854 -0.391492402 [361,] -0.107417755 1.003648854 [362,] -1.273829245 -0.107417755 [363,] -3.739044253 -1.273829245 [364,] 0.274800510 -3.739044253 [365,] -0.525600560 0.274800510 [366,] 0.420090755 -0.525600560 [367,] -0.011951211 0.420090755 [368,] -0.304336509 -0.011951211 [369,] 0.063998369 -0.304336509 [370,] 0.785119615 0.063998369 [371,] -0.073674072 0.785119615 [372,] -0.142984307 -0.073674072 [373,] -0.260431996 -0.142984307 [374,] -0.271927003 -0.260431996 [375,] 0.556492942 -0.271927003 [376,] 0.312585328 0.556492942 [377,] -0.218104437 0.312585328 [378,] 0.021895563 -0.218104437 [379,] 0.527182707 0.021895563 [380,] 0.164165383 0.527182707 [381,] -0.008162176 0.164165383 [382,] -0.756089780 -0.008162176 [383,] -0.815804188 -0.756089780 [384,] -1.762544068 -0.815804188 [385,] -4.429099436 -1.762544068 [386,] -4.913940156 -4.429099436 [387,] -5.396902842 -4.913940156 [388,] -5.620950725 -5.396902842 [389,] -6.386280665 -5.620950725 [390,] -6.022559218 -6.386280665 [391,] -0.035776878 -6.022559218 [392,] -0.491753786 -0.035776878 [393,] 1.136894012 -0.491753786 [394,] 0.673217335 1.136894012 [395,] -0.082674506 0.673217335 [396,] -0.004604096 -0.082674506 [397,] 0.350543343 -0.004604096 [398,] 0.221175369 0.350543343 [399,] 0.541375895 0.221175369 [400,] -0.327183717 0.541375895 [401,] -0.002413122 -0.327183717 [402,] -0.729338059 -0.002413122 [403,] 0.773047238 -0.729338059 [404,] -0.174567464 0.773047238 [405,] -0.382586338 -0.174567464 [406,] 0.402816283 -0.382586338 [407,] -0.387125978 0.402816283 [408,] -0.160316518 -0.387125978 [409,] -10.049718136 -0.160316518 [410,] -7.013190096 -10.049718136 [411,] -1.991177470 -7.013190096 [412,] -5.492387410 -1.991177470 [413,] 0.189531410 -5.492387410 [414,] -2.757390972 0.189531410 [415,] -6.398519491 -2.757390972 [416,] -2.173103413 -6.398519491 [417,] -1.902771922 -2.173103413 [418,] -0.411322286 -1.902771922 [419,] -0.915403117 -0.411322286 [420,] -0.124828830 -0.915403117 [421,] -0.440517044 -0.124828830 [422,] -0.433303412 -0.440517044 [423,] -0.235229900 -0.433303412 [424,] 0.745833607 -0.235229900 [425,] 0.176894012 0.745833607 [426,] -1.661578014 0.176894012 [427,] 0.320570652 -1.661578014 [428,] 0.656979042 0.320570652 [429,] 0.746805825 0.656979042 [430,] 1.356979042 0.746805825 [431,] 0.379996365 1.356979042 [432,] 0.921318156 0.379996365 [433,] 1.589738101 0.921318156 [434,] 0.715082983 1.589738101 [435,] 0.341117630 0.715082983 [436,] -0.533221465 0.341117630 [437,] -0.570435097 -0.533221465 [438,] 0.528215803 -0.570435097 [439,] 0.023560685 0.528215803 [440,] -0.263364252 0.023560685 [441,] -0.475634072 -0.263364252 [442,] -0.122732226 -0.475634072 [443,] -0.485807289 -0.122732226 [444,] -0.708134848 -0.485807289 [445,] 9.680386807 -0.708134848 [446,] 5.239851784 9.680386807 [447,] 1.873762631 5.239851784 [448,] -9.108920983 1.873762631 [449,] -3.586893019 -9.108920983 [450,] -14.494274829 -3.586893019 [451,] -12.782180687 -14.494274829 [452,] -10.891846677 -12.782180687 [453,] -1.722907048 -10.891846677 [454,] 0.787026584 -1.722907048 [455,] 8.646975723 0.787026584 [456,] 6.299573498 8.646975723 [457,] 1.029200357 6.299573498 [458,] 16.526065883 1.029200357 [459,] 0.902398981 16.526065883 [460,] -2.859102266 0.902398981 [461,] 10.958188371 -2.859102266 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.575484035 0.865198442 2 1.706577971 0.575484035 3 0.663903979 1.706577971 4 1.175599512 0.663903979 5 2.348732313 1.175599512 6 0.861634159 2.348732313 7 0.788501358 0.861634159 8 1.651749637 0.788501358 9 -0.367271866 1.651749637 10 -0.472042462 -0.367271866 11 -0.904600976 -0.472042462 12 -0.686928535 -0.904600976 13 -0.501410436 -0.686928535 14 -0.843853472 -0.501410436 15 -0.818107519 -0.843853472 16 -0.855263412 -0.818107519 17 -0.968739545 -0.855263412 18 -1.242303828 -0.968739545 19 -0.547499720 -1.242303828 20 -0.846351146 -0.547499720 21 -0.433908110 -0.846351146 22 -0.645776859 -0.433908110 23 -0.575922766 -0.645776859 24 -0.274801521 -0.575922766 25 0.169969075 -0.274801521 26 -0.146554792 0.169969075 27 0.852466711 -0.146554792 28 0.709595295 0.852466711 29 0.447152258 0.709595295 30 0.535398986 0.447152258 31 0.779337030 0.535398986 32 0.765945964 0.779337030 33 2.074709241 0.765945964 34 0.115399005 2.074709241 35 0.234997935 0.115399005 36 -0.339487068 0.234997935 37 -0.152589458 -0.339487068 38 0.473703472 -0.152589458 39 1.440400556 0.473703472 40 -0.209714922 1.440400556 41 -0.228107538 -0.209714922 42 1.191491391 -0.228107538 43 -0.534801521 1.191491391 44 -0.203163726 -0.534801521 45 0.501120712 -0.203163726 46 0.479798922 0.501120712 47 2.030430948 0.479798922 48 1.703047201 2.030430948 49 0.488507561 1.703047201 50 1.466295479 0.488507561 51 1.490689231 1.466295479 52 0.060084533 1.490689231 53 0.197298165 0.060084533 54 1.399890210 0.197298165 55 -0.848046698 1.399890210 56 -0.081437764 -0.848046698 57 -0.767995143 -0.081437764 58 -0.988888535 -0.767995143 59 -1.222282702 -0.988888535 60 -0.957396629 -1.222282702 61 -1.650274248 -0.957396629 62 -1.730803182 -1.650274248 63 -0.782422425 -1.730803182 64 -0.840158808 -0.782422425 65 5.045769646 -0.840158808 66 0.647121848 5.045769646 67 0.674250431 0.647121848 68 1.216292416 0.674250431 69 1.673217354 1.216292416 70 -0.654339610 1.673217354 71 0.374824718 -0.654339610 72 0.030169601 0.374824718 73 0.260859365 0.030169601 74 0.478589545 0.260859365 75 0.785341248 0.478589545 76 1.126031012 0.785341248 77 0.693703453 1.126031012 78 0.831375895 0.693703453 79 0.764450957 0.831375895 80 0.071436754 0.764450957 81 -0.330948544 0.071436754 82 -0.405087113 -0.330948544 83 0.822126518 -0.405087113 84 0.069224672 0.822126518 85 0.226322827 0.069224672 86 -0.029137533 0.226322827 87 0.275459845 -0.029137533 88 0.641953283 0.275459845 89 -0.386895023 0.641953283 90 -0.803877699 -0.386895023 91 1.277817834 -0.803877699 92 0.410145392 1.277817834 93 -0.195889255 0.410145392 94 0.029455628 -0.195889255 95 0.227128069 0.029455628 96 0.063363242 0.227128069 97 0.061667709 0.063363242 98 0.262241996 0.061667709 99 -0.532644077 0.262241996 100 0.617355923 -0.532644077 101 0.606322827 0.617355923 102 -0.074251461 0.606322827 103 0.110862467 -0.074251461 104 -0.011580570 0.110862467 105 0.559452508 -0.011580570 106 0.818820482 0.559452508 107 -0.609225683 0.818820482 108 -0.237329624 -0.609225683 109 -0.077071341 -0.237329624 110 -0.461209910 -0.077071341 111 -0.638824612 -0.461209910 112 -0.436211461 -0.638824612 113 0.900312406 -0.436211461 114 0.628501377 0.900312406 115 0.772755424 0.628501377 116 -0.393880763 0.772755424 117 -4.109082782 -0.393880763 118 -2.315147840 -4.109082782 119 -2.062008874 -2.315147840 120 -0.773619416 -2.062008874 121 0.288759642 -0.773619416 122 0.507465179 0.288759642 123 0.927410542 0.507465179 124 -3.982504278 0.927410542 125 -0.492154838 -3.982504278 126 -0.757615198 -0.492154838 127 -0.826007815 -0.757615198 128 -0.541179480 -0.826007815 129 -0.498678705 -0.541179480 130 -0.763449300 -0.498678705 131 -0.705892337 -0.763449300 132 -0.985433528 -0.705892337 133 -0.150605193 -0.985433528 134 1.028413246 -0.150605193 135 -1.146588304 1.028413246 136 -0.218113722 -1.146588304 137 -0.609320035 -0.218113722 138 -0.627648729 -0.609320035 139 -0.820982056 -0.627648729 140 -0.586992476 -0.820982056 141 -0.736305813 -0.586992476 142 -1.504005563 -0.736305813 143 -0.647788415 -1.504005563 144 -0.691583671 -0.647788415 145 1.017149195 -0.691583671 146 0.172931761 1.017149195 147 -0.198590556 0.172931761 148 -0.400401566 -0.198590556 149 -0.190401566 -0.400401566 150 0.523387450 -0.190401566 151 0.360889776 0.523387450 152 2.108042549 0.360889776 153 0.674134935 2.108042549 154 1.270859346 0.674134935 155 0.849163813 1.270859346 156 0.831059872 0.849163813 157 0.650427865 0.831059872 158 0.718100306 0.650427865 159 0.729795839 0.718100306 160 0.639106075 0.729795839 161 -0.057448222 0.639106075 162 -0.103169948 -0.057448222 163 4.737030578 -0.103169948 164 1.089042133 4.737030578 165 0.358668391 1.089042133 166 0.342712608 0.358668391 167 1.331549111 0.342712608 168 0.727006351 1.331549111 169 0.221114510 0.727006351 170 0.850291281 0.221114510 171 -0.890887704 0.850291281 172 0.578538009 -0.890887704 173 -0.123273002 0.578538009 174 0.224168484 -0.123273002 175 -0.041060920 0.224168484 176 0.044283962 -0.041060920 177 0.113709675 0.044283962 178 -0.430544372 0.113709675 179 -7.911881256 -0.430544372 180 -4.194727393 -7.911881256 181 -3.044851648 -4.194727393 182 -0.597296093 -3.044851648 183 -5.976890982 -0.597296093 184 0.046034132 -5.976890982 185 -0.220173731 0.046034132 186 -0.177156408 -0.220173731 187 0.561205798 -0.177156408 188 0.533648835 0.561205798 189 0.516091871 0.533648835 190 0.153132287 0.516091871 191 -0.042528599 0.153132287 192 -0.370201041 -0.042528599 193 1.086781617 -0.370201041 194 0.032041451 1.086781617 195 0.402041451 0.032041451 196 1.189944848 0.402041451 197 -0.082355402 1.189944848 198 1.168218885 -0.082355402 199 1.289136504 1.168218885 200 1.370750071 1.289136504 201 0.524457159 1.370750071 202 -0.697876564 0.524457159 203 -1.150662932 -0.697876564 204 -2.918977229 -1.150662932 205 -0.316527464 -2.918977229 206 -0.175861926 -0.316527464 207 -0.604254543 -0.175861926 208 -0.608566329 -0.604254543 209 0.005860935 -0.608566329 210 0.271524922 0.005860935 211 -0.894026689 0.271524922 212 -1.060751101 -0.894026689 213 -0.158396232 -1.060751101 214 0.332898230 -0.158396232 215 0.094277759 0.332898230 216 0.187237344 0.094277759 217 -0.262306948 0.187237344 218 -0.743343127 -0.262306948 219 -0.610526348 -0.743343127 220 1.259510265 -0.610526348 221 -0.310489735 1.259510265 222 -0.674974737 -0.310489735 223 0.123992166 -0.674974737 224 -0.193163726 0.123992166 225 -0.371841936 -0.193163726 226 0.346951751 -0.371841936 227 -0.370924317 0.346951751 228 -0.329286523 -0.370924317 229 0.202038369 -0.329286523 230 -0.758535918 0.202038369 231 -0.654886569 -0.758535918 232 -0.230088664 -0.654886569 233 -0.222416223 -0.230088664 234 0.340285078 -0.222416223 235 0.946377464 0.340285078 236 -0.235375808 0.946377464 237 0.094566454 -0.235375808 238 -0.204339610 0.094566454 239 -0.987846153 -0.204339610 240 -1.005779961 -0.987846153 241 -0.644427759 -1.005779961 242 0.080516052 -0.644427759 243 -0.676697579 0.080516052 244 -0.439140616 -0.676697579 245 -0.509772642 -0.439140616 246 -0.250404668 -0.509772642 247 0.567468281 -0.250404668 248 -0.025549043 0.567468281 249 1.627526019 -0.025549043 250 0.814450957 1.627526019 251 0.511433633 0.814450957 252 0.476836255 0.511433633 253 1.202439402 0.476836255 254 0.261433633 1.202439402 255 0.545572203 0.261433633 256 -0.148800404 0.545572203 257 -0.068481299 -0.148800404 258 0.102296634 -0.068481299 259 -0.108362702 0.102296634 260 0.124770100 -0.108362702 261 -0.785172162 0.124770100 262 -1.119459721 -0.785172162 263 -0.487992042 -1.119459721 264 -0.324023588 -0.487992042 265 0.402734298 -0.324023588 266 0.693682328 0.402734298 267 0.730060306 0.693682328 268 1.093019891 0.730060306 269 0.525979476 1.093019891 270 0.746611502 0.525979476 271 1.335833588 0.746611502 272 0.633420962 1.335833588 273 0.282296615 0.633420962 274 -0.069453537 0.282296615 275 -0.465804188 -0.069453537 276 -0.458131746 -0.465804188 277 -0.201033592 -0.458131746 278 -0.129283422 -0.201033592 279 0.260862467 -0.129283422 280 0.976322827 0.260862467 281 -0.121781096 0.976322827 282 3.639336954 -0.121781096 283 2.730026757 3.639336954 284 1.110285022 2.730026757 285 8.898701865 1.110285022 286 2.696350079 8.898701865 287 2.519020970 2.696350079 288 1.968392064 2.519020970 289 5.838793135 1.968392064 290 1.471467126 5.838793135 291 1.599598377 1.471467126 292 0.659880906 1.599598377 293 -0.508973621 0.659880906 294 1.700828936 -0.508973621 295 -0.043883921 1.700828936 296 -0.150462425 -0.043883921 297 0.403013708 -0.150462425 298 0.850081432 0.403013708 299 0.554736550 0.850081432 300 0.408759642 0.554736550 301 0.781290846 0.408759642 302 0.628331262 0.781290846 303 0.161549111 0.628331262 304 1.076893993 0.161549111 305 0.567583758 1.076893993 306 0.665198461 0.567583758 307 1.343244644 0.665198461 308 0.865687681 1.343244644 309 0.824049886 0.865687681 310 -0.245002046 0.824049886 311 -0.572674488 -0.245002046 312 -1.285779961 -0.572674488 313 -0.363510141 -1.285779961 314 0.069194262 -0.363510141 315 -0.461322286 0.069194262 316 0.143390570 -0.461322286 317 0.236751225 0.143390570 318 -0.302589439 0.236751225 319 0.027650782 -0.302589439 320 0.688656550 0.027650782 321 1.870467561 0.688656550 322 1.626098036 1.870467561 323 1.138656550 1.626098036 324 1.407277021 1.138656550 325 1.201327441 1.407277021 326 0.854138036 1.201327441 327 1.004229286 0.854138036 328 0.181871317 1.004229286 329 0.158449822 0.181871317 330 6.465742318 0.158449822 331 0.224766960 6.465742318 332 0.565572203 0.224766960 333 0.708735415 0.565572203 334 5.305660352 0.708735415 335 0.557355885 5.305660352 336 1.494766942 0.557355885 337 0.500692332 1.494766942 338 -0.127700284 0.500692332 339 1.860892877 -0.127700284 340 0.471837805 1.860892877 341 0.777410542 0.471837805 342 0.292928641 0.777410542 343 0.480169601 0.292928641 344 0.323761211 0.480169601 345 0.165405208 0.323761211 346 -0.344257644 0.165405208 347 -0.750061336 -0.344257644 348 -0.453938539 -0.750061336 349 -0.097186818 -0.453938539 350 0.048158064 -0.097186818 351 -0.431267649 0.048158064 352 0.112323962 -0.431267649 353 -0.432215678 0.112323962 354 -1.207019785 -0.432215678 355 0.281351705 -1.207019785 356 -0.926262997 0.281351705 357 0.072843611 -0.926262997 358 0.424770100 0.072843611 359 -0.391492402 0.424770100 360 1.003648854 -0.391492402 361 -0.107417755 1.003648854 362 -1.273829245 -0.107417755 363 -3.739044253 -1.273829245 364 0.274800510 -3.739044253 365 -0.525600560 0.274800510 366 0.420090755 -0.525600560 367 -0.011951211 0.420090755 368 -0.304336509 -0.011951211 369 0.063998369 -0.304336509 370 0.785119615 0.063998369 371 -0.073674072 0.785119615 372 -0.142984307 -0.073674072 373 -0.260431996 -0.142984307 374 -0.271927003 -0.260431996 375 0.556492942 -0.271927003 376 0.312585328 0.556492942 377 -0.218104437 0.312585328 378 0.021895563 -0.218104437 379 0.527182707 0.021895563 380 0.164165383 0.527182707 381 -0.008162176 0.164165383 382 -0.756089780 -0.008162176 383 -0.815804188 -0.756089780 384 -1.762544068 -0.815804188 385 -4.429099436 -1.762544068 386 -4.913940156 -4.429099436 387 -5.396902842 -4.913940156 388 -5.620950725 -5.396902842 389 -6.386280665 -5.620950725 390 -6.022559218 -6.386280665 391 -0.035776878 -6.022559218 392 -0.491753786 -0.035776878 393 1.136894012 -0.491753786 394 0.673217335 1.136894012 395 -0.082674506 0.673217335 396 -0.004604096 -0.082674506 397 0.350543343 -0.004604096 398 0.221175369 0.350543343 399 0.541375895 0.221175369 400 -0.327183717 0.541375895 401 -0.002413122 -0.327183717 402 -0.729338059 -0.002413122 403 0.773047238 -0.729338059 404 -0.174567464 0.773047238 405 -0.382586338 -0.174567464 406 0.402816283 -0.382586338 407 -0.387125978 0.402816283 408 -0.160316518 -0.387125978 409 -10.049718136 -0.160316518 410 -7.013190096 -10.049718136 411 -1.991177470 -7.013190096 412 -5.492387410 -1.991177470 413 0.189531410 -5.492387410 414 -2.757390972 0.189531410 415 -6.398519491 -2.757390972 416 -2.173103413 -6.398519491 417 -1.902771922 -2.173103413 418 -0.411322286 -1.902771922 419 -0.915403117 -0.411322286 420 -0.124828830 -0.915403117 421 -0.440517044 -0.124828830 422 -0.433303412 -0.440517044 423 -0.235229900 -0.433303412 424 0.745833607 -0.235229900 425 0.176894012 0.745833607 426 -1.661578014 0.176894012 427 0.320570652 -1.661578014 428 0.656979042 0.320570652 429 0.746805825 0.656979042 430 1.356979042 0.746805825 431 0.379996365 1.356979042 432 0.921318156 0.379996365 433 1.589738101 0.921318156 434 0.715082983 1.589738101 435 0.341117630 0.715082983 436 -0.533221465 0.341117630 437 -0.570435097 -0.533221465 438 0.528215803 -0.570435097 439 0.023560685 0.528215803 440 -0.263364252 0.023560685 441 -0.475634072 -0.263364252 442 -0.122732226 -0.475634072 443 -0.485807289 -0.122732226 444 -0.708134848 -0.485807289 445 9.680386807 -0.708134848 446 5.239851784 9.680386807 447 1.873762631 5.239851784 448 -9.108920983 1.873762631 449 -3.586893019 -9.108920983 450 -14.494274829 -3.586893019 451 -12.782180687 -14.494274829 452 -10.891846677 -12.782180687 453 -1.722907048 -10.891846677 454 0.787026584 -1.722907048 455 8.646975723 0.787026584 456 6.299573498 8.646975723 457 1.029200357 6.299573498 458 16.526065883 1.029200357 459 0.902398981 16.526065883 460 -2.859102266 0.902398981 461 10.958188371 -2.859102266 > 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/7061z1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8alzo1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9sxwq1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10uhle1462484259.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ') + if (rownames(mysum$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.row.start(a) > a<-table.element(a, mywarning) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11l51q1462484259.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$coefficients)[i],header=TRUE) + a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+')) + a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' ')) + a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+')) + a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' ')) + a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' ')) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/125c9h1462484259.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,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[2],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, signif(mysum$fstatistic[3],6)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' ')) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13k0v01462484259.tab") > if(n < 200) { + 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,formatC(signif(x[i],6),format='g',flag=' ')) + a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' ')) + a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' ')) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/147agr1462484259.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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' ')) + a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' ')) + a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' ')) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/15hpfj1462484259.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,signif(numsignificant1,6)) + a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' ')) + 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,signif(numsignificant5,6)) + a<-table.element(a,signif(numsignificant5/numgqtests,6)) + 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,signif(numsignificant10,6)) + a<-table.element(a,signif(numsignificant10/numgqtests,6)) + 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/16pgj21462484259.tab") + } + } > > try(system("convert tmp/1odwu1462484259.ps tmp/1odwu1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/28dyn1462484259.ps tmp/28dyn1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/3gua71462484259.ps tmp/3gua71462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/4yu8n1462484259.ps tmp/4yu8n1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/545l11462484259.ps tmp/545l11462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/6yert1462484259.ps tmp/6yert1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/7061z1462484259.ps tmp/7061z1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/8alzo1462484259.ps tmp/8alzo1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/9sxwq1462484259.ps tmp/9sxwq1462484259.png",intern=TRUE)) character(0) > try(system("convert tmp/10uhle1462484259.ps tmp/10uhle1462484259.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.212 0.755 6.007