R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(170650 + ,334 + ,95556 + ,86621 + ,223 + ,54565 + ,122154 + ,395 + ,63016 + ,152521 + ,876 + ,79774 + ,86318 + ,189 + ,31258 + ,37257 + ,111 + ,52491 + ,316392 + ,1317 + ,91256 + ,32750 + ,102 + ,22807 + ,116502 + ,580 + ,77411 + ,130554 + ,421 + ,48821 + ,173368 + ,539 + ,52295 + ,128294 + ,359 + ,63262 + ,111635 + ,463 + ,50466 + ,193105 + ,694 + ,62932 + ,143900 + ,396 + ,38439 + ,262290 + ,1184 + ,70817 + ,181110 + ,486 + ,105965 + ,202871 + ,788 + ,73795 + ,113853 + ,338 + ,82043 + ,159968 + ,486 + ,74349 + ,174585 + ,476 + ,82204 + ,291865 + ,828 + ,55709 + ,96067 + ,280 + ,37137 + ,110856 + ,334 + ,70780 + ,146342 + ,850 + ,55027 + ,146853 + ,710 + ,56699 + ,166051 + ,721 + ,65911 + ,172853 + ,408 + ,56316 + ,106888 + ,406 + ,26982 + ,193791 + ,591 + ,54628 + ,189408 + ,596 + ,96750 + ,136021 + ,411 + ,53009 + ,215469 + ,541 + ,64664 + ,75339 + ,207 + ,36990 + ,247979 + ,859 + ,85224 + ,167255 + ,669 + ,37048 + ,266277 + ,753 + ,59635 + 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+ ,185368 + ,582 + ,38885 + ,0 + ,0 + ,0 + ,203 + ,0 + ,0 + ,7199 + ,74 + ,1644 + ,46660 + ,259 + ,6179 + ,17547 + ,69 + ,3926 + ,73567 + ,187 + ,23238 + ,969 + ,0 + ,0 + ,105477 + ,341 + ,49288) + ,dim=c(3 + ,164) + ,dimnames=list(c('Time_RFC' + ,'Compendium_Views' + ,'Characters') + ,1:164)) > y <- array(NA,dim=c(3,164),dimnames=list(c('Time_RFC','Compendium_Views','Characters'),1:164)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '3' > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Characters Time_RFC Compendium_Views t 1 95556 170650 334 1 2 54565 86621 223 2 3 63016 122154 395 3 4 79774 152521 876 4 5 31258 86318 189 5 6 52491 37257 111 6 7 91256 316392 1317 7 8 22807 32750 102 8 9 77411 116502 580 9 10 48821 130554 421 10 11 52295 173368 539 11 12 63262 128294 359 12 13 50466 111635 463 13 14 62932 193105 694 14 15 38439 143900 396 15 16 70817 262290 1184 16 17 105965 181110 486 17 18 73795 202871 788 18 19 82043 113853 338 19 20 74349 159968 486 20 21 82204 174585 476 21 22 55709 291865 828 22 23 37137 96067 280 23 24 70780 110856 334 24 25 55027 146342 850 25 26 56699 146853 710 26 27 65911 166051 721 27 28 56316 172853 408 28 29 26982 106888 406 29 30 54628 193791 591 30 31 96750 189408 596 31 32 53009 136021 411 32 33 64664 215469 541 33 34 36990 75339 207 34 35 85224 247979 859 35 36 37048 167255 669 36 37 59635 266277 753 37 38 42051 122024 368 38 39 26998 80964 216 39 40 63717 214975 782 40 41 55071 225469 1094 41 42 40001 123008 464 42 43 54506 140190 474 43 44 35838 81106 300 44 45 50838 93125 836 45 46 86997 318604 1443 46 47 33032 78800 330 47 48 61704 158835 477 48 49 117986 228655 1042 49 50 56733 131108 646 50 51 55064 128744 343 51 52 5950 24188 218 52 53 84607 265554 598 53 54 32551 65029 255 54 55 31701 98066 434 55 56 71170 173587 654 56 57 101773 180360 482 57 58 101653 197266 753 58 59 81493 212179 693 59 60 55901 146062 478 60 61 109104 250805 843 61 62 114425 209228 832 62 63 36311 145696 710 63 64 70027 182854 613 64 65 73713 142064 390 65 66 40671 122105 332 66 67 89041 118675 421 67 68 57231 145285 636 68 69 68608 155015 576 69 70 59155 96487 410 70 71 55827 118807 468 71 72 22618 69471 364 72 73 58425 126630 449 73 74 65724 146344 530 74 75 56979 110652 373 75 76 72369 197814 618 76 77 79194 206788 640 77 78 202316 112604 283 78 79 44970 91921 297 79 80 49319 124190 457 80 81 36252 103304 453 81 82 75741 287032 883 82 83 38417 132798 570 83 84 64102 143272 355 84 85 56622 80953 437 85 86 15430 109237 641 86 87 72571 98875 252 87 88 67271 226212 944 88 89 43460 175829 559 89 90 99501 118217 736 90 91 28340 140433 465 91 92 76013 152193 450 92 93 37361 121798 429 93 94 48204 169631 736 94 95 76168 187732 586 95 96 85168 130533 387 96 97 125410 142339 397 97 98 123328 202077 575 98 99 83038 209419 728 99 100 120087 252260 943 100 101 91939 163066 447 101 102 103646 190562 617 102 103 29467 106351 341 103 104 43750 43287 214 104 105 34497 127493 507 105 106 66477 130005 451 106 107 71181 149006 616 107 108 74482 197727 694 108 109 174949 74112 215 109 110 46765 94968 360 110 111 90257 191351 422 111 112 51370 145048 442 112 113 1168 22938 154 113 114 51360 125927 474 114 115 25162 61857 192 115 116 21067 98969 340 116 117 58233 259571 832 117 118 855 21054 146 118 119 85903 174409 597 119 120 14116 31414 200 120 121 57637 193178 777 121 122 94137 137544 388 122 123 62147 77166 248 123 124 62832 82724 371 124 125 8773 38214 276 125 126 63785 90961 298 126 127 65196 197612 624 127 128 73087 137107 313 128 129 72631 251103 1040 129 130 86281 209835 609 130 131 162365 263825 819 131 132 56530 139144 344 132 133 35606 76470 312 133 134 70111 197114 642 134 135 92046 291962 1074 135 136 63989 51025 226 136 137 104911 254843 1176 137 138 43448 104554 510 138 139 60029 168059 391 139 140 38650 136745 534 140 141 47261 84092 256 141 142 73586 251448 1159 142 143 83042 152366 446 143 144 37238 173260 716 144 145 63958 204966 594 145 146 78956 83932 414 146 147 99518 139409 678 147 148 111436 185455 537 148 149 0 0 0 149 150 6023 14688 85 150 151 0 98 0 151 152 0 455 0 152 153 0 0 0 153 154 0 0 0 154 155 42564 137891 450 155 156 38885 185368 582 156 157 0 0 0 157 158 0 203 0 158 159 1644 7199 74 159 160 6179 46660 259 160 161 3926 17547 69 161 162 23238 73567 187 162 163 0 969 0 163 164 49288 105477 341 164 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Time_RFC Compendium_Views t 20240.3666 0.3842 -26.9450 -12.0325 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -54101 -17229 -5750 10788 147373 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.024e+04 6.575e+03 3.078 0.00245 ** Time_RFC 3.842e-01 6.193e-02 6.205 4.51e-09 *** Compendium_Views -2.694e+01 1.602e+01 -1.682 0.09456 . t -1.203e+01 4.472e+01 -0.269 0.78821 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 26120 on 160 degrees of freedom Multiple R-squared: 0.4036, Adjusted R-squared: 0.3925 F-statistic: 36.1 on 3 and 160 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,] 2.611215e-01 5.222431e-01 7.388785e-01 [2,] 1.313431e-01 2.626863e-01 8.686569e-01 [3,] 2.265975e-01 4.531950e-01 7.734025e-01 [4,] 1.330721e-01 2.661443e-01 8.669279e-01 [5,] 7.409438e-02 1.481888e-01 9.259056e-01 [6,] 6.413355e-02 1.282671e-01 9.358664e-01 [7,] 3.526680e-02 7.053360e-02 9.647332e-01 [8,] 1.825570e-02 3.651141e-02 9.817443e-01 [9,] 1.036271e-02 2.072543e-02 9.896373e-01 [10,] 5.128774e-03 1.025755e-02 9.948712e-01 [11,] 7.052129e-02 1.410426e-01 9.294787e-01 [12,] 4.631700e-02 9.263401e-02 9.536830e-01 [13,] 6.243365e-02 1.248673e-01 9.375664e-01 [14,] 4.226210e-02 8.452421e-02 9.577379e-01 [15,] 2.895101e-02 5.790201e-02 9.710490e-01 [16,] 5.778576e-02 1.155715e-01 9.422142e-01 [17,] 4.600979e-02 9.201959e-02 9.539902e-01 [18,] 3.813679e-02 7.627359e-02 9.618632e-01 [19,] 2.569419e-02 5.138838e-02 9.743058e-01 [20,] 1.664113e-02 3.328227e-02 9.833589e-01 [21,] 1.061442e-02 2.122884e-02 9.893856e-01 [22,] 7.079837e-03 1.415967e-02 9.929202e-01 [23,] 7.395568e-03 1.479114e-02 9.926044e-01 [24,] 5.039910e-03 1.007982e-02 9.949601e-01 [25,] 9.130303e-03 1.826061e-02 9.908697e-01 [26,] 5.847743e-03 1.169549e-02 9.941523e-01 [27,] 3.946090e-03 7.892181e-03 9.960539e-01 [28,] 2.506015e-03 5.012030e-03 9.974940e-01 [29,] 1.762406e-03 3.524813e-03 9.982376e-01 [30,] 1.740697e-03 3.481394e-03 9.982593e-01 [31,] 1.688024e-03 3.376048e-03 9.983120e-01 [32,] 1.083725e-03 2.167449e-03 9.989163e-01 [33,] 7.632140e-04 1.526428e-03 9.992368e-01 [34,] 4.915350e-04 9.830701e-04 9.995085e-01 [35,] 3.238872e-04 6.477743e-04 9.996761e-01 [36,] 1.987306e-04 3.974612e-04 9.998013e-01 [37,] 1.297590e-04 2.595181e-04 9.998702e-01 [38,] 7.542012e-05 1.508402e-04 9.999246e-01 [39,] 5.727936e-05 1.145587e-04 9.999427e-01 [40,] 3.756606e-05 7.513212e-05 9.999624e-01 [41,] 2.128448e-05 4.256897e-05 9.999787e-01 [42,] 1.518844e-05 3.037688e-05 9.999848e-01 [43,] 2.149417e-04 4.298834e-04 9.997851e-01 [44,] 1.352317e-04 2.704635e-04 9.998648e-01 [45,] 8.930261e-05 1.786052e-04 9.999107e-01 [46,] 8.578662e-05 1.715732e-04 9.999142e-01 [47,] 7.839314e-05 1.567863e-04 9.999216e-01 [48,] 4.734981e-05 9.469963e-05 9.999527e-01 [49,] 3.147604e-05 6.295207e-05 9.999685e-01 [50,] 2.415404e-05 4.830808e-05 9.999758e-01 [51,] 8.898045e-05 1.779609e-04 9.999110e-01 [52,] 1.765375e-04 3.530750e-04 9.998235e-01 [53,] 1.250920e-04 2.501841e-04 9.998749e-01 [54,] 8.146784e-05 1.629357e-04 9.999185e-01 [55,] 9.696176e-05 1.939235e-04 9.999030e-01 [56,] 2.487672e-04 4.975344e-04 9.997512e-01 [57,] 2.420800e-04 4.841600e-04 9.997579e-01 [58,] 1.602888e-04 3.205777e-04 9.998397e-01 [59,] 1.187773e-04 2.375546e-04 9.998812e-01 [60,] 1.007569e-04 2.015137e-04 9.998992e-01 [61,] 1.716966e-04 3.433933e-04 9.998283e-01 [62,] 1.095682e-04 2.191365e-04 9.998904e-01 [63,] 6.999653e-05 1.399931e-04 9.999300e-01 [64,] 4.614120e-05 9.228239e-05 9.999539e-01 [65,] 2.819007e-05 5.638014e-05 9.999718e-01 [66,] 2.491901e-05 4.983802e-05 9.999751e-01 [67,] 1.528882e-05 3.057765e-05 9.999847e-01 [68,] 9.328514e-06 1.865703e-05 9.999907e-01 [69,] 5.608985e-06 1.121797e-05 9.999944e-01 [70,] 3.661161e-06 7.322322e-06 9.999963e-01 [71,] 2.317659e-06 4.635318e-06 9.999977e-01 [72,] 1.787747e-01 3.575494e-01 8.212253e-01 [73,] 1.555978e-01 3.111955e-01 8.444022e-01 [74,] 1.366905e-01 2.733809e-01 8.633095e-01 [75,] 1.257140e-01 2.514281e-01 8.742860e-01 [76,] 1.479319e-01 2.958638e-01 8.520681e-01 [77,] 1.448872e-01 2.897744e-01 8.551128e-01 [78,] 1.245881e-01 2.491762e-01 8.754119e-01 [79,] 1.054960e-01 2.109921e-01 8.945040e-01 [80,] 1.275018e-01 2.550037e-01 8.724982e-01 [81,] 1.109792e-01 2.219583e-01 8.890208e-01 [82,] 1.033989e-01 2.067979e-01 8.966011e-01 [83,] 1.267904e-01 2.535807e-01 8.732096e-01 [84,] 1.940839e-01 3.881678e-01 8.059161e-01 [85,] 2.496012e-01 4.992024e-01 7.503988e-01 [86,] 2.181837e-01 4.363675e-01 7.818163e-01 [87,] 2.231783e-01 4.463566e-01 7.768217e-01 [88,] 2.221833e-01 4.443665e-01 7.778167e-01 [89,] 2.003831e-01 4.007662e-01 7.996169e-01 [90,] 1.831655e-01 3.663310e-01 8.168345e-01 [91,] 2.920563e-01 5.841127e-01 7.079437e-01 [92,] 3.179909e-01 6.359817e-01 6.820091e-01 [93,] 2.824295e-01 5.648590e-01 7.175705e-01 [94,] 2.720139e-01 5.440277e-01 7.279861e-01 [95,] 2.423622e-01 4.847244e-01 7.576378e-01 [96,] 2.249095e-01 4.498191e-01 7.750905e-01 [97,] 2.433121e-01 4.866242e-01 7.566879e-01 [98,] 2.094617e-01 4.189234e-01 7.905383e-01 [99,] 2.199427e-01 4.398853e-01 7.800573e-01 [100,] 1.865971e-01 3.731941e-01 8.134029e-01 [101,] 1.566290e-01 3.132580e-01 8.433710e-01 [102,] 1.351159e-01 2.702318e-01 8.648841e-01 [103,] 9.646791e-01 7.064185e-02 3.532092e-02 [104,] 9.551287e-01 8.974252e-02 4.487126e-02 [105,] 9.424254e-01 1.151492e-01 5.757458e-02 [106,] 9.337714e-01 1.324573e-01 6.622865e-02 [107,] 9.362946e-01 1.274109e-01 6.370544e-02 [108,] 9.210207e-01 1.579587e-01 7.897933e-02 [109,] 9.106691e-01 1.786618e-01 8.933089e-02 [110,] 9.247537e-01 1.504927e-01 7.524634e-02 [111,] 9.681002e-01 6.379957e-02 3.189979e-02 [112,] 9.726758e-01 5.464849e-02 2.732424e-02 [113,] 9.636305e-01 7.273904e-02 3.636952e-02 [114,] 9.605753e-01 7.884938e-02 3.942469e-02 [115,] 9.645029e-01 7.099414e-02 3.549707e-02 [116,] 9.621723e-01 7.565543e-02 3.782771e-02 [117,] 9.523471e-01 9.530582e-02 4.765291e-02 [118,] 9.431327e-01 1.137347e-01 5.686733e-02 [119,] 9.445209e-01 1.109583e-01 5.547913e-02 [120,] 9.298476e-01 1.403049e-01 7.015244e-02 [121,] 9.269621e-01 1.460758e-01 7.303789e-02 [122,] 9.045195e-01 1.909609e-01 9.548045e-02 [123,] 9.149202e-01 1.701597e-01 8.507983e-02 [124,] 8.918517e-01 2.162966e-01 1.081483e-01 [125,] 9.775225e-01 4.495498e-02 2.247749e-02 [126,] 9.688096e-01 6.238073e-02 3.119037e-02 [127,] 9.590644e-01 8.187114e-02 4.093557e-02 [128,] 9.472493e-01 1.055014e-01 5.275072e-02 [129,] 9.412061e-01 1.175879e-01 5.879393e-02 [130,] 9.486527e-01 1.026947e-01 5.134733e-02 [131,] 9.308262e-01 1.383476e-01 6.917381e-02 [132,] 9.066029e-01 1.867942e-01 9.339708e-02 [133,] 8.835756e-01 2.328489e-01 1.164244e-01 [134,] 8.826371e-01 2.347258e-01 1.173629e-01 [135,] 8.428749e-01 3.142502e-01 1.571251e-01 [136,] 8.787147e-01 2.425706e-01 1.212853e-01 [137,] 8.657835e-01 2.684330e-01 1.342165e-01 [138,] 9.792224e-01 4.155522e-02 2.077761e-02 [139,] 9.830213e-01 3.395736e-02 1.697868e-02 [140,] 9.825634e-01 3.487311e-02 1.743656e-02 [141,] 9.947822e-01 1.043566e-02 5.217829e-03 [142,] 9.999950e-01 1.006650e-05 5.033249e-06 [143,] 9.999818e-01 3.636256e-05 1.818128e-05 [144,] 9.999535e-01 9.303621e-05 4.651811e-05 [145,] 9.998439e-01 3.122800e-04 1.561400e-04 [146,] 9.994931e-01 1.013845e-03 5.069227e-04 [147,] 9.984680e-01 3.064041e-03 1.532021e-03 [148,] 9.958688e-01 8.262393e-03 4.131196e-03 [149,] 9.946511e-01 1.069771e-02 5.348855e-03 [150,] 9.932569e-01 1.348617e-02 6.743085e-03 [151,] 9.728803e-01 5.423940e-02 2.711970e-02 > postscript(file="/var/wessaorg/rcomp/tmp/15r671321954879.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/2xyzb1321954879.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/39bmz1321954879.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/48t2r1321954879.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5ip3y1321954879.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 164 Frequency = 1 1 2 3 4 5 6 18757.37964 7074.50279 6519.00420 24581.46147 -16996.10474 20998.23170 7 8 9 10 11 12 -14982.87991 -7172.45554 28142.71905 -10118.78331 -19903.93314 3544.06805 13 14 15 16 17 18 -36.63358 -12638.03653 -26242.26070 -18109.32171 29435.42263 -2946.53100 19 20 21 22 23 24 27392.20585 5979.04115 7960.24400 -54101.31627 -12194.44725 17233.14425 25 26 27 28 29 30 1760.77009 -523.83614 1620.02493 -19010.28865 -23040.00727 -23788.43336 31 32 33 34 35 36 20164.43104 -8036.13730 -23393.05541 -6211.62450 -6732.01181 -28998.44082 37 38 39 40 41 42 -42183.86571 -14702.42191 -18062.28589 -17572.28061 -21831.59577 -14495.66444 43 44 45 46 47 48 -6311.12821 -6953.30857 17883.08656 -16227.47869 -8028.81379 -6136.21425 49 50 51 52 53 54 38554.34991 4124.26474 -4788.69056 -17084.58099 -20918.01156 -5155.14192 55 56 57 58 59 60 -13863.97234 2527.05115 25905.11941 26603.33869 -891.44024 -6860.03088 61 62 63 64 65 66 15943.86213 36955.88723 -20022.07288 -3185.14877 10177.15150 -16746.65387 67 68 69 70 71 72 35351.40988 -877.91622 5155.80091 13730.54490 3401.23365 -13641.33386 73 74 75 76 77 78 2505.46490 4424.20712 5175.03860 -6312.20721 -2330.52103 147373.06090 79 80 81 82 83 84 -1636.52056 -5363.21179 -10500.80253 -30008.38100 -16491.83908 -612.46204 85 86 87 88 89 90 18074.27068 -28476.66130 22176.23795 -13393.29996 -28207.10522 54751.79881 91 92 93 94 95 96 -32235.44284 10526.79795 -17000.15535 -16252.18956 727.04045 26354.95098 97 98 99 100 101 102 62342.14084 42114.87555 3138.42457 29531.56123 22302.45561 28037.17318 103 104 105 106 107 108 -21209.69065 13894.80194 -19806.28381 9711.62981 11572.70884 -1732.92232 109 110 111 112 113 114 133336.82946 1058.25125 9199.03654 -11345.74455 -22376.78135 -3122.46118 115 116 117 118 119 120 -12288.89540 -26643.78188 -37917.92738 -22121.27763 16166.39313 -11361.87166 121 122 123 124 125 126 -14437.17821 32969.86082 20419.01061 22294.68823 -17209.69840 18139.81801 127 128 129 130 131 132 -12632.26493 10139.09515 -14517.27454 3388.13949 64397.70233 -6317.17030 133 134 135 136 137 138 -4009.75887 -6956.67868 -9813.45664 31868.96154 20086.45629 -1563.38342 139 140 141 142 143 144 -12577.71869 -18059.58594 3303.93534 -10331.96376 17995.20210 -28549.85742 145 146 147 148 149 150 -17287.70166 39377.87882 45749.11018 36187.36510 -18447.52604 -15765.83300 151 152 153 154 155 156 -18461.11621 -18586.25603 -18399.39609 -18387.36360 -16668.80970 -35021.42338 157 158 159 160 161 162 -18351.26614 -18417.23360 -17455.39049 -23085.88431 -19260.12617 -18281.49883 163 164 -18651.39607 -318.88653 > postscript(file="/var/wessaorg/rcomp/tmp/6yg8n1321954879.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 = 164 Frequency = 1 lag(myerror, k = 1) myerror 0 18757.37964 NA 1 7074.50279 18757.37964 2 6519.00420 7074.50279 3 24581.46147 6519.00420 4 -16996.10474 24581.46147 5 20998.23170 -16996.10474 6 -14982.87991 20998.23170 7 -7172.45554 -14982.87991 8 28142.71905 -7172.45554 9 -10118.78331 28142.71905 10 -19903.93314 -10118.78331 11 3544.06805 -19903.93314 12 -36.63358 3544.06805 13 -12638.03653 -36.63358 14 -26242.26070 -12638.03653 15 -18109.32171 -26242.26070 16 29435.42263 -18109.32171 17 -2946.53100 29435.42263 18 27392.20585 -2946.53100 19 5979.04115 27392.20585 20 7960.24400 5979.04115 21 -54101.31627 7960.24400 22 -12194.44725 -54101.31627 23 17233.14425 -12194.44725 24 1760.77009 17233.14425 25 -523.83614 1760.77009 26 1620.02493 -523.83614 27 -19010.28865 1620.02493 28 -23040.00727 -19010.28865 29 -23788.43336 -23040.00727 30 20164.43104 -23788.43336 31 -8036.13730 20164.43104 32 -23393.05541 -8036.13730 33 -6211.62450 -23393.05541 34 -6732.01181 -6211.62450 35 -28998.44082 -6732.01181 36 -42183.86571 -28998.44082 37 -14702.42191 -42183.86571 38 -18062.28589 -14702.42191 39 -17572.28061 -18062.28589 40 -21831.59577 -17572.28061 41 -14495.66444 -21831.59577 42 -6311.12821 -14495.66444 43 -6953.30857 -6311.12821 44 17883.08656 -6953.30857 45 -16227.47869 17883.08656 46 -8028.81379 -16227.47869 47 -6136.21425 -8028.81379 48 38554.34991 -6136.21425 49 4124.26474 38554.34991 50 -4788.69056 4124.26474 51 -17084.58099 -4788.69056 52 -20918.01156 -17084.58099 53 -5155.14192 -20918.01156 54 -13863.97234 -5155.14192 55 2527.05115 -13863.97234 56 25905.11941 2527.05115 57 26603.33869 25905.11941 58 -891.44024 26603.33869 59 -6860.03088 -891.44024 60 15943.86213 -6860.03088 61 36955.88723 15943.86213 62 -20022.07288 36955.88723 63 -3185.14877 -20022.07288 64 10177.15150 -3185.14877 65 -16746.65387 10177.15150 66 35351.40988 -16746.65387 67 -877.91622 35351.40988 68 5155.80091 -877.91622 69 13730.54490 5155.80091 70 3401.23365 13730.54490 71 -13641.33386 3401.23365 72 2505.46490 -13641.33386 73 4424.20712 2505.46490 74 5175.03860 4424.20712 75 -6312.20721 5175.03860 76 -2330.52103 -6312.20721 77 147373.06090 -2330.52103 78 -1636.52056 147373.06090 79 -5363.21179 -1636.52056 80 -10500.80253 -5363.21179 81 -30008.38100 -10500.80253 82 -16491.83908 -30008.38100 83 -612.46204 -16491.83908 84 18074.27068 -612.46204 85 -28476.66130 18074.27068 86 22176.23795 -28476.66130 87 -13393.29996 22176.23795 88 -28207.10522 -13393.29996 89 54751.79881 -28207.10522 90 -32235.44284 54751.79881 91 10526.79795 -32235.44284 92 -17000.15535 10526.79795 93 -16252.18956 -17000.15535 94 727.04045 -16252.18956 95 26354.95098 727.04045 96 62342.14084 26354.95098 97 42114.87555 62342.14084 98 3138.42457 42114.87555 99 29531.56123 3138.42457 100 22302.45561 29531.56123 101 28037.17318 22302.45561 102 -21209.69065 28037.17318 103 13894.80194 -21209.69065 104 -19806.28381 13894.80194 105 9711.62981 -19806.28381 106 11572.70884 9711.62981 107 -1732.92232 11572.70884 108 133336.82946 -1732.92232 109 1058.25125 133336.82946 110 9199.03654 1058.25125 111 -11345.74455 9199.03654 112 -22376.78135 -11345.74455 113 -3122.46118 -22376.78135 114 -12288.89540 -3122.46118 115 -26643.78188 -12288.89540 116 -37917.92738 -26643.78188 117 -22121.27763 -37917.92738 118 16166.39313 -22121.27763 119 -11361.87166 16166.39313 120 -14437.17821 -11361.87166 121 32969.86082 -14437.17821 122 20419.01061 32969.86082 123 22294.68823 20419.01061 124 -17209.69840 22294.68823 125 18139.81801 -17209.69840 126 -12632.26493 18139.81801 127 10139.09515 -12632.26493 128 -14517.27454 10139.09515 129 3388.13949 -14517.27454 130 64397.70233 3388.13949 131 -6317.17030 64397.70233 132 -4009.75887 -6317.17030 133 -6956.67868 -4009.75887 134 -9813.45664 -6956.67868 135 31868.96154 -9813.45664 136 20086.45629 31868.96154 137 -1563.38342 20086.45629 138 -12577.71869 -1563.38342 139 -18059.58594 -12577.71869 140 3303.93534 -18059.58594 141 -10331.96376 3303.93534 142 17995.20210 -10331.96376 143 -28549.85742 17995.20210 144 -17287.70166 -28549.85742 145 39377.87882 -17287.70166 146 45749.11018 39377.87882 147 36187.36510 45749.11018 148 -18447.52604 36187.36510 149 -15765.83300 -18447.52604 150 -18461.11621 -15765.83300 151 -18586.25603 -18461.11621 152 -18399.39609 -18586.25603 153 -18387.36360 -18399.39609 154 -16668.80970 -18387.36360 155 -35021.42338 -16668.80970 156 -18351.26614 -35021.42338 157 -18417.23360 -18351.26614 158 -17455.39049 -18417.23360 159 -23085.88431 -17455.39049 160 -19260.12617 -23085.88431 161 -18281.49883 -19260.12617 162 -18651.39607 -18281.49883 163 -318.88653 -18651.39607 164 NA -318.88653 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 7074.50279 18757.37964 [2,] 6519.00420 7074.50279 [3,] 24581.46147 6519.00420 [4,] -16996.10474 24581.46147 [5,] 20998.23170 -16996.10474 [6,] -14982.87991 20998.23170 [7,] -7172.45554 -14982.87991 [8,] 28142.71905 -7172.45554 [9,] -10118.78331 28142.71905 [10,] -19903.93314 -10118.78331 [11,] 3544.06805 -19903.93314 [12,] -36.63358 3544.06805 [13,] -12638.03653 -36.63358 [14,] -26242.26070 -12638.03653 [15,] -18109.32171 -26242.26070 [16,] 29435.42263 -18109.32171 [17,] -2946.53100 29435.42263 [18,] 27392.20585 -2946.53100 [19,] 5979.04115 27392.20585 [20,] 7960.24400 5979.04115 [21,] -54101.31627 7960.24400 [22,] -12194.44725 -54101.31627 [23,] 17233.14425 -12194.44725 [24,] 1760.77009 17233.14425 [25,] -523.83614 1760.77009 [26,] 1620.02493 -523.83614 [27,] -19010.28865 1620.02493 [28,] -23040.00727 -19010.28865 [29,] -23788.43336 -23040.00727 [30,] 20164.43104 -23788.43336 [31,] -8036.13730 20164.43104 [32,] -23393.05541 -8036.13730 [33,] -6211.62450 -23393.05541 [34,] -6732.01181 -6211.62450 [35,] -28998.44082 -6732.01181 [36,] -42183.86571 -28998.44082 [37,] -14702.42191 -42183.86571 [38,] -18062.28589 -14702.42191 [39,] -17572.28061 -18062.28589 [40,] -21831.59577 -17572.28061 [41,] -14495.66444 -21831.59577 [42,] -6311.12821 -14495.66444 [43,] -6953.30857 -6311.12821 [44,] 17883.08656 -6953.30857 [45,] -16227.47869 17883.08656 [46,] -8028.81379 -16227.47869 [47,] -6136.21425 -8028.81379 [48,] 38554.34991 -6136.21425 [49,] 4124.26474 38554.34991 [50,] -4788.69056 4124.26474 [51,] -17084.58099 -4788.69056 [52,] -20918.01156 -17084.58099 [53,] -5155.14192 -20918.01156 [54,] -13863.97234 -5155.14192 [55,] 2527.05115 -13863.97234 [56,] 25905.11941 2527.05115 [57,] 26603.33869 25905.11941 [58,] -891.44024 26603.33869 [59,] -6860.03088 -891.44024 [60,] 15943.86213 -6860.03088 [61,] 36955.88723 15943.86213 [62,] -20022.07288 36955.88723 [63,] -3185.14877 -20022.07288 [64,] 10177.15150 -3185.14877 [65,] -16746.65387 10177.15150 [66,] 35351.40988 -16746.65387 [67,] -877.91622 35351.40988 [68,] 5155.80091 -877.91622 [69,] 13730.54490 5155.80091 [70,] 3401.23365 13730.54490 [71,] -13641.33386 3401.23365 [72,] 2505.46490 -13641.33386 [73,] 4424.20712 2505.46490 [74,] 5175.03860 4424.20712 [75,] -6312.20721 5175.03860 [76,] -2330.52103 -6312.20721 [77,] 147373.06090 -2330.52103 [78,] -1636.52056 147373.06090 [79,] -5363.21179 -1636.52056 [80,] -10500.80253 -5363.21179 [81,] -30008.38100 -10500.80253 [82,] -16491.83908 -30008.38100 [83,] -612.46204 -16491.83908 [84,] 18074.27068 -612.46204 [85,] -28476.66130 18074.27068 [86,] 22176.23795 -28476.66130 [87,] -13393.29996 22176.23795 [88,] -28207.10522 -13393.29996 [89,] 54751.79881 -28207.10522 [90,] -32235.44284 54751.79881 [91,] 10526.79795 -32235.44284 [92,] -17000.15535 10526.79795 [93,] -16252.18956 -17000.15535 [94,] 727.04045 -16252.18956 [95,] 26354.95098 727.04045 [96,] 62342.14084 26354.95098 [97,] 42114.87555 62342.14084 [98,] 3138.42457 42114.87555 [99,] 29531.56123 3138.42457 [100,] 22302.45561 29531.56123 [101,] 28037.17318 22302.45561 [102,] -21209.69065 28037.17318 [103,] 13894.80194 -21209.69065 [104,] -19806.28381 13894.80194 [105,] 9711.62981 -19806.28381 [106,] 11572.70884 9711.62981 [107,] -1732.92232 11572.70884 [108,] 133336.82946 -1732.92232 [109,] 1058.25125 133336.82946 [110,] 9199.03654 1058.25125 [111,] -11345.74455 9199.03654 [112,] -22376.78135 -11345.74455 [113,] -3122.46118 -22376.78135 [114,] -12288.89540 -3122.46118 [115,] -26643.78188 -12288.89540 [116,] -37917.92738 -26643.78188 [117,] -22121.27763 -37917.92738 [118,] 16166.39313 -22121.27763 [119,] -11361.87166 16166.39313 [120,] -14437.17821 -11361.87166 [121,] 32969.86082 -14437.17821 [122,] 20419.01061 32969.86082 [123,] 22294.68823 20419.01061 [124,] -17209.69840 22294.68823 [125,] 18139.81801 -17209.69840 [126,] -12632.26493 18139.81801 [127,] 10139.09515 -12632.26493 [128,] -14517.27454 10139.09515 [129,] 3388.13949 -14517.27454 [130,] 64397.70233 3388.13949 [131,] -6317.17030 64397.70233 [132,] -4009.75887 -6317.17030 [133,] -6956.67868 -4009.75887 [134,] -9813.45664 -6956.67868 [135,] 31868.96154 -9813.45664 [136,] 20086.45629 31868.96154 [137,] -1563.38342 20086.45629 [138,] -12577.71869 -1563.38342 [139,] -18059.58594 -12577.71869 [140,] 3303.93534 -18059.58594 [141,] -10331.96376 3303.93534 [142,] 17995.20210 -10331.96376 [143,] -28549.85742 17995.20210 [144,] -17287.70166 -28549.85742 [145,] 39377.87882 -17287.70166 [146,] 45749.11018 39377.87882 [147,] 36187.36510 45749.11018 [148,] -18447.52604 36187.36510 [149,] -15765.83300 -18447.52604 [150,] -18461.11621 -15765.83300 [151,] -18586.25603 -18461.11621 [152,] -18399.39609 -18586.25603 [153,] -18387.36360 -18399.39609 [154,] -16668.80970 -18387.36360 [155,] -35021.42338 -16668.80970 [156,] -18351.26614 -35021.42338 [157,] -18417.23360 -18351.26614 [158,] -17455.39049 -18417.23360 [159,] -23085.88431 -17455.39049 [160,] -19260.12617 -23085.88431 [161,] -18281.49883 -19260.12617 [162,] -18651.39607 -18281.49883 [163,] -318.88653 -18651.39607 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 7074.50279 18757.37964 2 6519.00420 7074.50279 3 24581.46147 6519.00420 4 -16996.10474 24581.46147 5 20998.23170 -16996.10474 6 -14982.87991 20998.23170 7 -7172.45554 -14982.87991 8 28142.71905 -7172.45554 9 -10118.78331 28142.71905 10 -19903.93314 -10118.78331 11 3544.06805 -19903.93314 12 -36.63358 3544.06805 13 -12638.03653 -36.63358 14 -26242.26070 -12638.03653 15 -18109.32171 -26242.26070 16 29435.42263 -18109.32171 17 -2946.53100 29435.42263 18 27392.20585 -2946.53100 19 5979.04115 27392.20585 20 7960.24400 5979.04115 21 -54101.31627 7960.24400 22 -12194.44725 -54101.31627 23 17233.14425 -12194.44725 24 1760.77009 17233.14425 25 -523.83614 1760.77009 26 1620.02493 -523.83614 27 -19010.28865 1620.02493 28 -23040.00727 -19010.28865 29 -23788.43336 -23040.00727 30 20164.43104 -23788.43336 31 -8036.13730 20164.43104 32 -23393.05541 -8036.13730 33 -6211.62450 -23393.05541 34 -6732.01181 -6211.62450 35 -28998.44082 -6732.01181 36 -42183.86571 -28998.44082 37 -14702.42191 -42183.86571 38 -18062.28589 -14702.42191 39 -17572.28061 -18062.28589 40 -21831.59577 -17572.28061 41 -14495.66444 -21831.59577 42 -6311.12821 -14495.66444 43 -6953.30857 -6311.12821 44 17883.08656 -6953.30857 45 -16227.47869 17883.08656 46 -8028.81379 -16227.47869 47 -6136.21425 -8028.81379 48 38554.34991 -6136.21425 49 4124.26474 38554.34991 50 -4788.69056 4124.26474 51 -17084.58099 -4788.69056 52 -20918.01156 -17084.58099 53 -5155.14192 -20918.01156 54 -13863.97234 -5155.14192 55 2527.05115 -13863.97234 56 25905.11941 2527.05115 57 26603.33869 25905.11941 58 -891.44024 26603.33869 59 -6860.03088 -891.44024 60 15943.86213 -6860.03088 61 36955.88723 15943.86213 62 -20022.07288 36955.88723 63 -3185.14877 -20022.07288 64 10177.15150 -3185.14877 65 -16746.65387 10177.15150 66 35351.40988 -16746.65387 67 -877.91622 35351.40988 68 5155.80091 -877.91622 69 13730.54490 5155.80091 70 3401.23365 13730.54490 71 -13641.33386 3401.23365 72 2505.46490 -13641.33386 73 4424.20712 2505.46490 74 5175.03860 4424.20712 75 -6312.20721 5175.03860 76 -2330.52103 -6312.20721 77 147373.06090 -2330.52103 78 -1636.52056 147373.06090 79 -5363.21179 -1636.52056 80 -10500.80253 -5363.21179 81 -30008.38100 -10500.80253 82 -16491.83908 -30008.38100 83 -612.46204 -16491.83908 84 18074.27068 -612.46204 85 -28476.66130 18074.27068 86 22176.23795 -28476.66130 87 -13393.29996 22176.23795 88 -28207.10522 -13393.29996 89 54751.79881 -28207.10522 90 -32235.44284 54751.79881 91 10526.79795 -32235.44284 92 -17000.15535 10526.79795 93 -16252.18956 -17000.15535 94 727.04045 -16252.18956 95 26354.95098 727.04045 96 62342.14084 26354.95098 97 42114.87555 62342.14084 98 3138.42457 42114.87555 99 29531.56123 3138.42457 100 22302.45561 29531.56123 101 28037.17318 22302.45561 102 -21209.69065 28037.17318 103 13894.80194 -21209.69065 104 -19806.28381 13894.80194 105 9711.62981 -19806.28381 106 11572.70884 9711.62981 107 -1732.92232 11572.70884 108 133336.82946 -1732.92232 109 1058.25125 133336.82946 110 9199.03654 1058.25125 111 -11345.74455 9199.03654 112 -22376.78135 -11345.74455 113 -3122.46118 -22376.78135 114 -12288.89540 -3122.46118 115 -26643.78188 -12288.89540 116 -37917.92738 -26643.78188 117 -22121.27763 -37917.92738 118 16166.39313 -22121.27763 119 -11361.87166 16166.39313 120 -14437.17821 -11361.87166 121 32969.86082 -14437.17821 122 20419.01061 32969.86082 123 22294.68823 20419.01061 124 -17209.69840 22294.68823 125 18139.81801 -17209.69840 126 -12632.26493 18139.81801 127 10139.09515 -12632.26493 128 -14517.27454 10139.09515 129 3388.13949 -14517.27454 130 64397.70233 3388.13949 131 -6317.17030 64397.70233 132 -4009.75887 -6317.17030 133 -6956.67868 -4009.75887 134 -9813.45664 -6956.67868 135 31868.96154 -9813.45664 136 20086.45629 31868.96154 137 -1563.38342 20086.45629 138 -12577.71869 -1563.38342 139 -18059.58594 -12577.71869 140 3303.93534 -18059.58594 141 -10331.96376 3303.93534 142 17995.20210 -10331.96376 143 -28549.85742 17995.20210 144 -17287.70166 -28549.85742 145 39377.87882 -17287.70166 146 45749.11018 39377.87882 147 36187.36510 45749.11018 148 -18447.52604 36187.36510 149 -15765.83300 -18447.52604 150 -18461.11621 -15765.83300 151 -18586.25603 -18461.11621 152 -18399.39609 -18586.25603 153 -18387.36360 -18399.39609 154 -16668.80970 -18387.36360 155 -35021.42338 -16668.80970 156 -18351.26614 -35021.42338 157 -18417.23360 -18351.26614 158 -17455.39049 -18417.23360 159 -23085.88431 -17455.39049 160 -19260.12617 -23085.88431 161 -18281.49883 -19260.12617 162 -18651.39607 -18281.49883 163 -318.88653 -18651.39607 > 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/7ysbk1321954879.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/8p2uu1321954879.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/9t12r1321954879.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/1001291321954879.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11dp9l1321954879.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12jbd11321954879.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/131gzz1321954879.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14w7nv1321954879.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/150zfp1321954879.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/161akv1321954879.tab") + } > > try(system("convert tmp/15r671321954879.ps tmp/15r671321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/2xyzb1321954879.ps tmp/2xyzb1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/39bmz1321954879.ps tmp/39bmz1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/48t2r1321954879.ps tmp/48t2r1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/5ip3y1321954879.ps tmp/5ip3y1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/6yg8n1321954879.ps tmp/6yg8n1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/7ysbk1321954879.ps tmp/7ysbk1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/8p2uu1321954879.ps tmp/8p2uu1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/9t12r1321954879.ps tmp/9t12r1321954879.png",intern=TRUE)) character(0) > try(system("convert tmp/1001291321954879.ps tmp/1001291321954879.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.716 0.688 5.454