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(1845 + ,162687 + ,95 + ,595 + ,115 + ,0 + ,48 + ,1917 + ,233285 + ,67 + ,580 + ,79 + ,1 + ,75 + ,192 + ,7215 + ,18 + ,72 + ,1 + ,0 + ,0 + ,2665 + ,164587 + ,99 + ,737 + ,158 + ,0 + ,74 + ,3709 + ,283430 + ,141 + ,1255 + ,127 + ,0 + ,92 + ,7138 + ,546996 + ,275 + ,2021 + ,278 + ,1 + ,137 + ,1888 + ,192501 + ,61 + ,606 + ,95 + ,1 + ,65 + ,1909 + ,213538 + ,64 + ,533 + ,64 + ,0 + ,97 + ,2140 + ,182282 + ,46 + ,687 + ,92 + ,0 + ,62 + ,3168 + ,336547 + ,102 + ,1074 + ,130 + ,1 + ,72 + ,1957 + ,122275 + ,77 + ,637 + ,158 + ,2 + ,50 + ,2370 + ,203938 + ,72 + ,743 + ,120 + ,0 + ,88 + ,1998 + ,119300 + ,110 + ,701 + ,87 + ,0 + ,68 + ,3203 + ,220796 + ,122 + ,1087 + ,264 + ,4 + ,79 + ,1505 + ,174005 + ,67 + ,422 + ,51 + ,4 + ,56 + ,1574 + ,156326 + ,89 + ,474 + ,85 + ,3 + ,54 + ,1965 + ,164063 + ,60 + ,483 + ,100 + ,0 + ,101 + ,1314 + ,90025 + ,63 + ,375 + ,72 + ,5 + ,13 + ,2921 + ,179987 + ,90 + ,929 + ,147 + ,0 + ,80 + ,823 + ,47066 + ,29 + ,262 + ,49 + 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,40 + ,174 + ,29 + ,3 + ,3 + ,285 + ,19764 + ,12 + ,75 + ,19 + ,1 + ,10 + ,1873 + ,177559 + ,57 + ,572 + ,64 + ,3 + ,47 + ,1269 + ,154169 + ,36 + ,414 + ,79 + ,0 + ,44 + ,1725 + ,164249 + ,54 + ,562 + ,104 + ,0 + ,54 + ,256 + ,11796 + ,9 + ,79 + ,22 + ,0 + ,1 + ,98 + ,10674 + ,9 + ,33 + ,7 + ,0 + ,0 + ,1435 + ,151322 + ,59 + ,487 + ,37 + ,0 + ,46 + ,41 + ,6836 + ,3 + ,11 + ,5 + ,0 + ,0 + ,1931 + ,174712 + ,68 + ,664 + ,48 + ,6 + ,51 + ,42 + ,5118 + ,3 + ,6 + ,1 + ,0 + ,5 + ,528 + ,40248 + ,16 + ,183 + ,34 + ,1 + ,8 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1122 + ,127628 + ,51 + ,342 + ,53 + ,0 + ,38 + ,1305 + ,88837 + ,38 + ,269 + ,44 + ,0 + ,21 + ,81 + ,7131 + ,4 + ,27 + ,0 + ,1 + ,0 + ,262 + ,9056 + ,15 + ,99 + ,18 + ,0 + ,0 + ,1165 + ,97191 + ,31 + ,322 + ,52 + ,1 + ,26 + ,1405 + ,157478 + ,59 + ,367 + ,60 + ,0 + ,53 + ,1409 + ,125583 + ,23 + ,521 + ,50 + ,1 + ,31) + ,dim=c(7 + ,144) + ,dimnames=list(c('a' + ,'b' + ,'c' + ,'d' + ,'e' + ,'f' + ,'g') + ,1:144)) > y <- array(NA,dim=c(7,144),dimnames=list(c('a','b','c','d','e','f','g'),1:144)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x a b c d e f g 1 1845 162687 95 595 115 0 48 2 1917 233285 67 580 79 1 75 3 192 7215 18 72 1 0 0 4 2665 164587 99 737 158 0 74 5 3709 283430 141 1255 127 0 92 6 7138 546996 275 2021 278 1 137 7 1888 192501 61 606 95 1 65 8 1909 213538 64 533 64 0 97 9 2140 182282 46 687 92 0 62 10 3168 336547 102 1074 130 1 72 11 1957 122275 77 637 158 2 50 12 2370 203938 72 743 120 0 88 13 1998 119300 110 701 87 0 68 14 3203 220796 122 1087 264 4 79 15 1505 174005 67 422 51 4 56 16 1574 156326 89 474 85 3 54 17 1965 164063 60 483 100 0 101 18 1314 90025 63 375 72 5 13 19 2921 179987 90 929 147 0 80 20 823 47066 29 262 49 0 19 21 1289 109572 64 437 40 0 33 22 2818 241285 103 850 99 0 99 23 1792 208339 77 652 127 1 38 24 2474 164166 59 754 166 1 68 25 1994 159763 89 619 41 1 54 26 1806 207078 34 657 160 0 63 27 2177 217028 169 695 92 0 66 28 1458 201536 96 366 59 0 90 29 3057 408960 124 1015 89 0 75 30 2487 250260 48 1029 104 0 68 31 1914 216527 46 576 81 0 69 32 1825 212949 51 656 116 2 80 33 2509 164248 110 812 105 4 59 34 3634 278911 136 1108 388 0 135 35 2608 238654 59 852 88 1 75 36 1 0 1 0 0 0 0 37 2157 233971 66 1009 63 0 54 38 1978 149649 55 658 138 3 62 39 2224 161703 52 547 270 9 46 40 2215 254893 70 826 64 0 83 41 2538 269492 73 838 96 2 106 42 1881 169526 62 704 62 0 51 43 1113 107893 35 404 35 2 27 44 2380 229714 83 848 66 1 78 45 1365 139667 51 419 56 2 71 46 1294 175983 102 349 46 2 44 47 756 81407 33 216 49 1 23 48 2465 251259 110 796 121 0 78 49 2327 239807 90 752 113 1 60 50 2787 172743 60 964 190 8 73 51 658 48188 28 205 37 0 12 52 2013 169355 71 506 52 0 104 53 2666 335398 78 841 89 0 95 54 2086 244729 81 699 73 0 57 55 2067 208286 62 746 61 1 68 56 1776 159913 58 547 77 8 44 57 2045 232137 72 561 63 0 62 58 1047 101694 26 329 75 1 26 59 1190 157258 68 427 32 0 67 60 2932 211586 101 993 59 10 36 61 1868 181076 66 564 71 6 56 62 2316 158024 86 858 92 0 55 63 1392 141491 64 376 87 11 54 64 1355 130108 40 471 48 3 61 65 1326 166420 39 432 63 0 27 66 1587 135509 45 500 41 0 64 67 2336 195043 72 504 86 8 76 68 2898 138708 66 887 152 2 93 69 1118 116552 40 271 49 0 59 70 340 31970 15 101 40 0 5 71 3224 291993 121 1203 148 3 62 72 1552 167825 82 506 86 1 47 73 1551 135926 69 528 62 2 88 74 1794 136647 77 501 96 1 57 75 2728 171518 71 698 95 0 81 76 1580 108980 46 426 83 2 35 77 2414 183471 61 709 112 1 102 78 2640 167426 101 847 77 0 73 79 1203 112510 49 367 78 0 32 80 1313 92421 77 413 114 0 34 81 1207 117169 84 272 55 0 80 82 2246 304603 65 830 60 0 49 83 1076 75101 30 334 49 1 30 84 1638 145043 41 524 132 0 57 85 1208 95827 48 393 49 0 54 86 1868 173931 60 574 71 0 38 87 2829 250424 252 695 102 0 63 88 1209 115367 116 284 74 0 58 89 1463 125839 66 462 49 7 49 90 1610 164078 54 653 74 0 46 91 1865 158931 42 684 59 5 51 92 2444 190382 85 714 91 1 90 93 1253 155226 59 420 68 0 45 94 1468 146159 61 551 81 0 28 95 979 62641 44 396 33 0 26 96 2365 258585 121 741 166 0 54 97 1890 199841 71 571 97 0 96 98 223 19349 12 67 15 0 13 99 2527 247280 109 877 105 3 43 100 2186 173152 88 885 61 0 46 101 778 72128 30 306 11 0 30 102 1194 104253 26 382 45 0 59 103 1424 151090 57 435 89 0 73 104 1386 147990 68 348 72 1 40 105 839 87448 42 227 27 1 36 106 596 27676 22 194 59 0 2 107 1684 170326 52 413 127 0 103 108 1168 132148 38 273 48 1 30 109 0 0 0 0 0 0 0 110 1315 133868 36 390 58 0 78 111 1149 109001 68 376 57 0 25 112 1485 158833 46 495 60 0 59 113 1529 150013 66 448 77 1 60 114 962 89887 63 313 71 0 36 115 78 3616 5 14 5 0 0 116 0 0 0 0 0 0 0 117 1295 216479 48 445 78 0 51 118 1751 177323 102 637 76 0 79 119 2142 177948 102 593 124 2 30 120 1070 140106 41 326 67 0 43 121 778 43410 19 292 63 0 7 122 1986 206059 76 573 92 1 92 123 1084 109873 45 315 58 0 32 124 2400 157084 61 683 65 10 84 125 731 60493 40 174 29 3 3 126 285 19764 12 75 19 1 10 127 1873 177559 57 572 64 3 47 128 1269 154169 36 414 79 0 44 129 1725 164249 54 562 104 0 54 130 256 11796 9 79 22 0 1 131 98 10674 9 33 7 0 0 132 1435 151322 59 487 37 0 46 133 41 6836 3 11 5 0 0 134 1931 174712 68 664 48 6 51 135 42 5118 3 6 1 0 5 136 528 40248 16 183 34 1 8 137 0 0 0 0 0 0 0 138 1122 127628 51 342 53 0 38 139 1305 88837 38 269 44 0 21 140 81 7131 4 27 0 1 0 141 262 9056 15 99 18 0 0 142 1165 97191 31 322 52 1 26 143 1405 157478 59 367 60 0 53 144 1409 125583 23 521 50 1 31 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) b c d e f -4.255e+01 6.808e-04 3.756e+00 1.939e+00 1.549e+00 2.139e+01 g 3.848e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -469.37 -101.03 -5.51 68.08 877.43 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -4.255e+01 3.179e+01 -1.338 0.183026 b 6.808e-04 4.241e-04 1.605 0.110755 c 3.756e+00 5.858e-01 6.412 2.15e-09 *** d 1.939e+00 1.182e-01 16.407 < 2e-16 *** e 1.549e+00 3.896e-01 3.977 0.000112 *** f 2.139e+01 6.549e+00 3.266 0.001379 ** g 3.848e+00 7.968e-01 4.829 3.62e-06 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 172.6 on 137 degrees of freedom Multiple R-squared: 0.9673, Adjusted R-squared: 0.9659 F-statistic: 675.4 on 6 and 137 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.9728030 5.439399e-02 2.719700e-02 [2,] 0.9472134 1.055731e-01 5.278655e-02 [3,] 0.9074797 1.850406e-01 9.252031e-02 [4,] 0.9104541 1.790917e-01 8.954587e-02 [5,] 0.8781991 2.436018e-01 1.218009e-01 [6,] 0.9235561 1.528879e-01 7.644394e-02 [7,] 0.8941455 2.117089e-01 1.058545e-01 [8,] 0.8856855 2.286290e-01 1.143145e-01 [9,] 0.9518437 9.631258e-02 4.815629e-02 [10,] 0.9553966 8.920686e-02 4.460343e-02 [11,] 0.9459731 1.080537e-01 5.402687e-02 [12,] 0.9245530 1.508941e-01 7.544703e-02 [13,] 0.9013471 1.973057e-01 9.865286e-02 [14,] 0.9442380 1.115240e-01 5.576202e-02 [15,] 0.9570795 8.584109e-02 4.292054e-02 [16,] 0.9429098 1.141804e-01 5.709019e-02 [17,] 0.9384698 1.230603e-01 6.153016e-02 [18,] 0.9819146 3.617088e-02 1.808544e-02 [19,] 0.9760367 4.792662e-02 2.396331e-02 [20,] 0.9737543 5.249140e-02 2.624570e-02 [21,] 0.9912802 1.743967e-02 8.719834e-03 [22,] 0.9902050 1.959007e-02 9.795036e-03 [23,] 0.9937619 1.247617e-02 6.238084e-03 [24,] 0.9908630 1.827404e-02 9.137020e-03 [25,] 0.9936602 1.267955e-02 6.339773e-03 [26,] 0.9927994 1.440117e-02 7.200583e-03 [27,] 0.9922474 1.550528e-02 7.752641e-03 [28,] 0.9997051 5.897057e-04 2.948529e-04 [29,] 0.9995478 9.044025e-04 4.522012e-04 [30,] 0.9995764 8.472716e-04 4.236358e-04 [31,] 0.9996040 7.920876e-04 3.960438e-04 [32,] 0.9994642 1.071529e-03 5.357645e-04 [33,] 0.9991807 1.638647e-03 8.193236e-04 [34,] 0.9987467 2.506589e-03 1.253295e-03 [35,] 0.9983449 3.310103e-03 1.655052e-03 [36,] 0.9977140 4.572053e-03 2.286027e-03 [37,] 0.9971065 5.786953e-03 2.893476e-03 [38,] 0.9960865 7.826932e-03 3.913466e-03 [39,] 0.9949140 1.017193e-02 5.085964e-03 [40,] 0.9926578 1.468433e-02 7.342167e-03 [41,] 0.9918467 1.630658e-02 8.153289e-03 [42,] 0.9900093 1.998138e-02 9.990690e-03 [43,] 0.9922438 1.551236e-02 7.756178e-03 [44,] 0.9896606 2.067888e-02 1.033944e-02 [45,] 0.9856279 2.874422e-02 1.437211e-02 [46,] 0.9811399 3.772029e-02 1.886015e-02 [47,] 0.9751713 4.965750e-02 2.482875e-02 [48,] 0.9832628 3.347431e-02 1.673715e-02 [49,] 0.9790340 4.193200e-02 2.096600e-02 [50,] 0.9839012 3.219770e-02 1.609885e-02 [51,] 0.9800266 3.994685e-02 1.997342e-02 [52,] 0.9731634 5.367325e-02 2.683663e-02 [53,] 0.9659555 6.808907e-02 3.404454e-02 [54,] 0.9774972 4.500565e-02 2.250282e-02 [55,] 0.9747669 5.046623e-02 2.523311e-02 [56,] 0.9690770 6.184610e-02 3.092305e-02 [57,] 0.9650273 6.994533e-02 3.497266e-02 [58,] 0.9881302 2.373954e-02 1.186977e-02 [59,] 0.9908709 1.825813e-02 9.129066e-03 [60,] 0.9890500 2.190000e-02 1.095000e-02 [61,] 0.9858948 2.821034e-02 1.410517e-02 [62,] 0.9896630 2.067410e-02 1.033705e-02 [63,] 0.9885035 2.299295e-02 1.149647e-02 [64,] 0.9926732 1.465367e-02 7.326834e-03 [65,] 0.9906085 1.878301e-02 9.391505e-03 [66,] 0.9999540 9.194729e-05 4.597365e-05 [67,] 0.9999750 4.990541e-05 2.495271e-05 [68,] 0.9999801 3.979528e-05 1.989764e-05 [69,] 0.9999947 1.061083e-05 5.305413e-06 [70,] 0.9999907 1.866434e-05 9.332169e-06 [71,] 0.9999862 2.750462e-05 1.375231e-05 [72,] 0.9999769 4.629474e-05 2.314737e-05 [73,] 0.9999599 8.010373e-05 4.005187e-05 [74,] 0.9999461 1.078818e-04 5.394090e-05 [75,] 0.9999077 1.845250e-04 9.226250e-05 [76,] 0.9998467 3.066536e-04 1.533268e-04 [77,] 0.9999235 1.529596e-04 7.647982e-05 [78,] 0.9999457 1.086259e-04 5.431293e-05 [79,] 0.9999190 1.620494e-04 8.102470e-05 [80,] 0.9999551 8.977124e-05 4.488562e-05 [81,] 0.9999551 8.970868e-05 4.485434e-05 [82,] 0.9999467 1.065174e-04 5.325868e-05 [83,] 0.9999873 2.539567e-05 1.269783e-05 [84,] 0.9999835 3.309096e-05 1.654548e-05 [85,] 0.9999760 4.802441e-05 2.401220e-05 [86,] 0.9999568 8.644923e-05 4.322461e-05 [87,] 0.9999500 1.000168e-04 5.000842e-05 [88,] 0.9999139 1.722140e-04 8.610700e-05 [89,] 0.9998540 2.919595e-04 1.459797e-04 [90,] 0.9998118 3.764540e-04 1.882270e-04 [91,] 0.9997132 5.736518e-04 2.868259e-04 [92,] 0.9995036 9.927184e-04 4.963592e-04 [93,] 0.9993432 1.313601e-03 6.568007e-04 [94,] 0.9990432 1.913589e-03 9.567944e-04 [95,] 0.9985660 2.867946e-03 1.433973e-03 [96,] 0.9976832 4.633516e-03 2.316758e-03 [97,] 0.9964720 7.055969e-03 3.527985e-03 [98,] 0.9944332 1.113366e-02 5.566831e-03 [99,] 0.9952405 9.519055e-03 4.759528e-03 [100,] 0.9926052 1.478956e-02 7.394778e-03 [101,] 0.9897908 2.041837e-02 1.020919e-02 [102,] 0.9847243 3.055131e-02 1.527565e-02 [103,] 0.9773514 4.529726e-02 2.264863e-02 [104,] 0.9664988 6.700238e-02 3.350119e-02 [105,] 0.9657769 6.844618e-02 3.422309e-02 [106,] 0.9510202 9.795967e-02 4.897983e-02 [107,] 0.9307335 1.385329e-01 6.926647e-02 [108,] 0.9692177 6.156466e-02 3.078233e-02 [109,] 0.9844153 3.116946e-02 1.558473e-02 [110,] 0.9765294 4.694113e-02 2.347057e-02 [111,] 0.9701399 5.972024e-02 2.986012e-02 [112,] 0.9555348 8.893048e-02 4.446524e-02 [113,] 0.9363071 1.273859e-01 6.369294e-02 [114,] 0.9067624 1.864752e-01 9.323758e-02 [115,] 0.9462936 1.074128e-01 5.370638e-02 [116,] 0.9503708 9.925837e-02 4.962919e-02 [117,] 0.9306278 1.387445e-01 6.937224e-02 [118,] 0.8907434 2.185131e-01 1.092566e-01 [119,] 0.9248182 1.503636e-01 7.518181e-02 [120,] 0.8744801 2.510398e-01 1.255199e-01 [121,] 0.8017155 3.965689e-01 1.982845e-01 [122,] 0.7458228 5.083543e-01 2.541772e-01 [123,] 0.6296839 7.406322e-01 3.703161e-01 [124,] 0.5223050 9.553899e-01 4.776950e-01 [125,] 0.5214214 9.571572e-01 4.785786e-01 > postscript(file="/var/wessaorg/rcomp/tmp/1jo431324618970.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2cko11324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/35kwi1324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4w9nv1324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5cin11324618970.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 = 144 Frequency = 1 1 2 3 4 5 6 -96.567289 -7.862591 20.871126 265.129498 44.890043 877.428858 7 8 9 10 11 12 -23.284171 59.957992 172.547132 16.080504 -87.967655 38.139148 13 14 15 16 17 18 -209.464737 -269.165927 -20.834067 -146.858047 190.440083 63.015136 19 20 21 22 23 24 166.145586 67.556544 -19.695660 127.020275 -225.052440 181.012940 25 26 27 28 29 30 100.613054 -184.299650 -307.041399 -144.601254 -39.093704 -239.020246 31 32 33 34 35 36 128.559063 -271.224667 -23.089419 -293.083769 168.213195 39.789867 37 38 39 40 41 42 -469.374496 -80.250347 112.744632 -198.959293 -101.284633 -82.024710 43 44 45 46 47 48 -33.576180 -113.553119 -94.226158 -126.422594 14.562866 -107.652208 49 50 51 52 53 54 -17.152156 -128.879878 61.591603 211.752583 53.191988 -30.028522 55 56 57 58 59 60 -89.092457 -28.454068 235.172693 47.124840 -265.220692 82.000495 61 62 63 64 65 66 -7.974726 -89.807317 -209.033503 -127.735458 69.654738 89.042107 67 68 69 70 71 72 401.343477 242.293642 102.575789 27.393945 -251.260622 -144.278369 73 74 75 76 77 78 -259.337714 93.453226 574.885463 243.555208 140.456557 146.758211 79 80 81 82 83 84 29.340598 -104.823797 -66.159565 -53.758488 94.403954 -12.020397 85 86 87 88 89 90 -40.670650 197.617681 6.493639 -151.194039 -137.970102 -219.736986 91 92 93 94 95 96 -79.193232 144.613976 -124.589404 -119.655333 -105.344628 -124.702347 97 98 99 100 101 102 -96.972367 4.131816 -100.939228 -207.308119 -67.018434 30.520056 103 104 105 106 107 108 -112.615498 110.782429 22.383454 61.810882 21.418963 237.336685 109 110 111 112 113 114 42.546225 -14.963754 -51.619929 -33.099682 -18.669630 -148.691813 115 116 117 118 119 120 64.411253 42.546225 -170.022303 -367.107754 180.164942 -38.182014 121 122 123 124 125 126 28.922335 -26.114408 58.971458 144.429519 124.106616 34.296523 127 128 129 130 131 132 127.351165 -23.036325 -5.679118 65.601951 24.643208 -25.651970 133 134 135 136 137 138 38.548438 -87.167881 37.372006 23.380621 42.546225 -5.342615 139 140 141 142 143 144 473.791451 29.929382 22.196928 198.617564 110.252403 51.363041 > postscript(file="/var/wessaorg/rcomp/tmp/6x7ao1324618970.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 = 144 Frequency = 1 lag(myerror, k = 1) myerror 0 -96.567289 NA 1 -7.862591 -96.567289 2 20.871126 -7.862591 3 265.129498 20.871126 4 44.890043 265.129498 5 877.428858 44.890043 6 -23.284171 877.428858 7 59.957992 -23.284171 8 172.547132 59.957992 9 16.080504 172.547132 10 -87.967655 16.080504 11 38.139148 -87.967655 12 -209.464737 38.139148 13 -269.165927 -209.464737 14 -20.834067 -269.165927 15 -146.858047 -20.834067 16 190.440083 -146.858047 17 63.015136 190.440083 18 166.145586 63.015136 19 67.556544 166.145586 20 -19.695660 67.556544 21 127.020275 -19.695660 22 -225.052440 127.020275 23 181.012940 -225.052440 24 100.613054 181.012940 25 -184.299650 100.613054 26 -307.041399 -184.299650 27 -144.601254 -307.041399 28 -39.093704 -144.601254 29 -239.020246 -39.093704 30 128.559063 -239.020246 31 -271.224667 128.559063 32 -23.089419 -271.224667 33 -293.083769 -23.089419 34 168.213195 -293.083769 35 39.789867 168.213195 36 -469.374496 39.789867 37 -80.250347 -469.374496 38 112.744632 -80.250347 39 -198.959293 112.744632 40 -101.284633 -198.959293 41 -82.024710 -101.284633 42 -33.576180 -82.024710 43 -113.553119 -33.576180 44 -94.226158 -113.553119 45 -126.422594 -94.226158 46 14.562866 -126.422594 47 -107.652208 14.562866 48 -17.152156 -107.652208 49 -128.879878 -17.152156 50 61.591603 -128.879878 51 211.752583 61.591603 52 53.191988 211.752583 53 -30.028522 53.191988 54 -89.092457 -30.028522 55 -28.454068 -89.092457 56 235.172693 -28.454068 57 47.124840 235.172693 58 -265.220692 47.124840 59 82.000495 -265.220692 60 -7.974726 82.000495 61 -89.807317 -7.974726 62 -209.033503 -89.807317 63 -127.735458 -209.033503 64 69.654738 -127.735458 65 89.042107 69.654738 66 401.343477 89.042107 67 242.293642 401.343477 68 102.575789 242.293642 69 27.393945 102.575789 70 -251.260622 27.393945 71 -144.278369 -251.260622 72 -259.337714 -144.278369 73 93.453226 -259.337714 74 574.885463 93.453226 75 243.555208 574.885463 76 140.456557 243.555208 77 146.758211 140.456557 78 29.340598 146.758211 79 -104.823797 29.340598 80 -66.159565 -104.823797 81 -53.758488 -66.159565 82 94.403954 -53.758488 83 -12.020397 94.403954 84 -40.670650 -12.020397 85 197.617681 -40.670650 86 6.493639 197.617681 87 -151.194039 6.493639 88 -137.970102 -151.194039 89 -219.736986 -137.970102 90 -79.193232 -219.736986 91 144.613976 -79.193232 92 -124.589404 144.613976 93 -119.655333 -124.589404 94 -105.344628 -119.655333 95 -124.702347 -105.344628 96 -96.972367 -124.702347 97 4.131816 -96.972367 98 -100.939228 4.131816 99 -207.308119 -100.939228 100 -67.018434 -207.308119 101 30.520056 -67.018434 102 -112.615498 30.520056 103 110.782429 -112.615498 104 22.383454 110.782429 105 61.810882 22.383454 106 21.418963 61.810882 107 237.336685 21.418963 108 42.546225 237.336685 109 -14.963754 42.546225 110 -51.619929 -14.963754 111 -33.099682 -51.619929 112 -18.669630 -33.099682 113 -148.691813 -18.669630 114 64.411253 -148.691813 115 42.546225 64.411253 116 -170.022303 42.546225 117 -367.107754 -170.022303 118 180.164942 -367.107754 119 -38.182014 180.164942 120 28.922335 -38.182014 121 -26.114408 28.922335 122 58.971458 -26.114408 123 144.429519 58.971458 124 124.106616 144.429519 125 34.296523 124.106616 126 127.351165 34.296523 127 -23.036325 127.351165 128 -5.679118 -23.036325 129 65.601951 -5.679118 130 24.643208 65.601951 131 -25.651970 24.643208 132 38.548438 -25.651970 133 -87.167881 38.548438 134 37.372006 -87.167881 135 23.380621 37.372006 136 42.546225 23.380621 137 -5.342615 42.546225 138 473.791451 -5.342615 139 29.929382 473.791451 140 22.196928 29.929382 141 198.617564 22.196928 142 110.252403 198.617564 143 51.363041 110.252403 144 NA 51.363041 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -7.862591 -96.567289 [2,] 20.871126 -7.862591 [3,] 265.129498 20.871126 [4,] 44.890043 265.129498 [5,] 877.428858 44.890043 [6,] -23.284171 877.428858 [7,] 59.957992 -23.284171 [8,] 172.547132 59.957992 [9,] 16.080504 172.547132 [10,] -87.967655 16.080504 [11,] 38.139148 -87.967655 [12,] -209.464737 38.139148 [13,] -269.165927 -209.464737 [14,] -20.834067 -269.165927 [15,] -146.858047 -20.834067 [16,] 190.440083 -146.858047 [17,] 63.015136 190.440083 [18,] 166.145586 63.015136 [19,] 67.556544 166.145586 [20,] -19.695660 67.556544 [21,] 127.020275 -19.695660 [22,] -225.052440 127.020275 [23,] 181.012940 -225.052440 [24,] 100.613054 181.012940 [25,] -184.299650 100.613054 [26,] -307.041399 -184.299650 [27,] -144.601254 -307.041399 [28,] -39.093704 -144.601254 [29,] -239.020246 -39.093704 [30,] 128.559063 -239.020246 [31,] -271.224667 128.559063 [32,] -23.089419 -271.224667 [33,] -293.083769 -23.089419 [34,] 168.213195 -293.083769 [35,] 39.789867 168.213195 [36,] -469.374496 39.789867 [37,] -80.250347 -469.374496 [38,] 112.744632 -80.250347 [39,] -198.959293 112.744632 [40,] -101.284633 -198.959293 [41,] -82.024710 -101.284633 [42,] -33.576180 -82.024710 [43,] -113.553119 -33.576180 [44,] -94.226158 -113.553119 [45,] -126.422594 -94.226158 [46,] 14.562866 -126.422594 [47,] -107.652208 14.562866 [48,] -17.152156 -107.652208 [49,] -128.879878 -17.152156 [50,] 61.591603 -128.879878 [51,] 211.752583 61.591603 [52,] 53.191988 211.752583 [53,] -30.028522 53.191988 [54,] -89.092457 -30.028522 [55,] -28.454068 -89.092457 [56,] 235.172693 -28.454068 [57,] 47.124840 235.172693 [58,] -265.220692 47.124840 [59,] 82.000495 -265.220692 [60,] -7.974726 82.000495 [61,] -89.807317 -7.974726 [62,] -209.033503 -89.807317 [63,] -127.735458 -209.033503 [64,] 69.654738 -127.735458 [65,] 89.042107 69.654738 [66,] 401.343477 89.042107 [67,] 242.293642 401.343477 [68,] 102.575789 242.293642 [69,] 27.393945 102.575789 [70,] -251.260622 27.393945 [71,] -144.278369 -251.260622 [72,] -259.337714 -144.278369 [73,] 93.453226 -259.337714 [74,] 574.885463 93.453226 [75,] 243.555208 574.885463 [76,] 140.456557 243.555208 [77,] 146.758211 140.456557 [78,] 29.340598 146.758211 [79,] -104.823797 29.340598 [80,] -66.159565 -104.823797 [81,] -53.758488 -66.159565 [82,] 94.403954 -53.758488 [83,] -12.020397 94.403954 [84,] -40.670650 -12.020397 [85,] 197.617681 -40.670650 [86,] 6.493639 197.617681 [87,] -151.194039 6.493639 [88,] -137.970102 -151.194039 [89,] -219.736986 -137.970102 [90,] -79.193232 -219.736986 [91,] 144.613976 -79.193232 [92,] -124.589404 144.613976 [93,] -119.655333 -124.589404 [94,] -105.344628 -119.655333 [95,] -124.702347 -105.344628 [96,] -96.972367 -124.702347 [97,] 4.131816 -96.972367 [98,] -100.939228 4.131816 [99,] -207.308119 -100.939228 [100,] -67.018434 -207.308119 [101,] 30.520056 -67.018434 [102,] -112.615498 30.520056 [103,] 110.782429 -112.615498 [104,] 22.383454 110.782429 [105,] 61.810882 22.383454 [106,] 21.418963 61.810882 [107,] 237.336685 21.418963 [108,] 42.546225 237.336685 [109,] -14.963754 42.546225 [110,] -51.619929 -14.963754 [111,] -33.099682 -51.619929 [112,] -18.669630 -33.099682 [113,] -148.691813 -18.669630 [114,] 64.411253 -148.691813 [115,] 42.546225 64.411253 [116,] -170.022303 42.546225 [117,] -367.107754 -170.022303 [118,] 180.164942 -367.107754 [119,] -38.182014 180.164942 [120,] 28.922335 -38.182014 [121,] -26.114408 28.922335 [122,] 58.971458 -26.114408 [123,] 144.429519 58.971458 [124,] 124.106616 144.429519 [125,] 34.296523 124.106616 [126,] 127.351165 34.296523 [127,] -23.036325 127.351165 [128,] -5.679118 -23.036325 [129,] 65.601951 -5.679118 [130,] 24.643208 65.601951 [131,] -25.651970 24.643208 [132,] 38.548438 -25.651970 [133,] -87.167881 38.548438 [134,] 37.372006 -87.167881 [135,] 23.380621 37.372006 [136,] 42.546225 23.380621 [137,] -5.342615 42.546225 [138,] 473.791451 -5.342615 [139,] 29.929382 473.791451 [140,] 22.196928 29.929382 [141,] 198.617564 22.196928 [142,] 110.252403 198.617564 [143,] 51.363041 110.252403 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -7.862591 -96.567289 2 20.871126 -7.862591 3 265.129498 20.871126 4 44.890043 265.129498 5 877.428858 44.890043 6 -23.284171 877.428858 7 59.957992 -23.284171 8 172.547132 59.957992 9 16.080504 172.547132 10 -87.967655 16.080504 11 38.139148 -87.967655 12 -209.464737 38.139148 13 -269.165927 -209.464737 14 -20.834067 -269.165927 15 -146.858047 -20.834067 16 190.440083 -146.858047 17 63.015136 190.440083 18 166.145586 63.015136 19 67.556544 166.145586 20 -19.695660 67.556544 21 127.020275 -19.695660 22 -225.052440 127.020275 23 181.012940 -225.052440 24 100.613054 181.012940 25 -184.299650 100.613054 26 -307.041399 -184.299650 27 -144.601254 -307.041399 28 -39.093704 -144.601254 29 -239.020246 -39.093704 30 128.559063 -239.020246 31 -271.224667 128.559063 32 -23.089419 -271.224667 33 -293.083769 -23.089419 34 168.213195 -293.083769 35 39.789867 168.213195 36 -469.374496 39.789867 37 -80.250347 -469.374496 38 112.744632 -80.250347 39 -198.959293 112.744632 40 -101.284633 -198.959293 41 -82.024710 -101.284633 42 -33.576180 -82.024710 43 -113.553119 -33.576180 44 -94.226158 -113.553119 45 -126.422594 -94.226158 46 14.562866 -126.422594 47 -107.652208 14.562866 48 -17.152156 -107.652208 49 -128.879878 -17.152156 50 61.591603 -128.879878 51 211.752583 61.591603 52 53.191988 211.752583 53 -30.028522 53.191988 54 -89.092457 -30.028522 55 -28.454068 -89.092457 56 235.172693 -28.454068 57 47.124840 235.172693 58 -265.220692 47.124840 59 82.000495 -265.220692 60 -7.974726 82.000495 61 -89.807317 -7.974726 62 -209.033503 -89.807317 63 -127.735458 -209.033503 64 69.654738 -127.735458 65 89.042107 69.654738 66 401.343477 89.042107 67 242.293642 401.343477 68 102.575789 242.293642 69 27.393945 102.575789 70 -251.260622 27.393945 71 -144.278369 -251.260622 72 -259.337714 -144.278369 73 93.453226 -259.337714 74 574.885463 93.453226 75 243.555208 574.885463 76 140.456557 243.555208 77 146.758211 140.456557 78 29.340598 146.758211 79 -104.823797 29.340598 80 -66.159565 -104.823797 81 -53.758488 -66.159565 82 94.403954 -53.758488 83 -12.020397 94.403954 84 -40.670650 -12.020397 85 197.617681 -40.670650 86 6.493639 197.617681 87 -151.194039 6.493639 88 -137.970102 -151.194039 89 -219.736986 -137.970102 90 -79.193232 -219.736986 91 144.613976 -79.193232 92 -124.589404 144.613976 93 -119.655333 -124.589404 94 -105.344628 -119.655333 95 -124.702347 -105.344628 96 -96.972367 -124.702347 97 4.131816 -96.972367 98 -100.939228 4.131816 99 -207.308119 -100.939228 100 -67.018434 -207.308119 101 30.520056 -67.018434 102 -112.615498 30.520056 103 110.782429 -112.615498 104 22.383454 110.782429 105 61.810882 22.383454 106 21.418963 61.810882 107 237.336685 21.418963 108 42.546225 237.336685 109 -14.963754 42.546225 110 -51.619929 -14.963754 111 -33.099682 -51.619929 112 -18.669630 -33.099682 113 -148.691813 -18.669630 114 64.411253 -148.691813 115 42.546225 64.411253 116 -170.022303 42.546225 117 -367.107754 -170.022303 118 180.164942 -367.107754 119 -38.182014 180.164942 120 28.922335 -38.182014 121 -26.114408 28.922335 122 58.971458 -26.114408 123 144.429519 58.971458 124 124.106616 144.429519 125 34.296523 124.106616 126 127.351165 34.296523 127 -23.036325 127.351165 128 -5.679118 -23.036325 129 65.601951 -5.679118 130 24.643208 65.601951 131 -25.651970 24.643208 132 38.548438 -25.651970 133 -87.167881 38.548438 134 37.372006 -87.167881 135 23.380621 37.372006 136 42.546225 23.380621 137 -5.342615 42.546225 138 473.791451 -5.342615 139 29.929382 473.791451 140 22.196928 29.929382 141 198.617564 22.196928 142 110.252403 198.617564 143 51.363041 110.252403 > 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/7pzvw1324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8025k1324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9r9o31324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10td5z1324618970.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11x2it1324618970.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/12b5pn1324618970.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/13ocom1324618970.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/14jzb81324618970.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/15z6501324618970.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/169al01324618970.tab") + } > > try(system("convert tmp/1jo431324618970.ps tmp/1jo431324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/2cko11324618970.ps tmp/2cko11324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/35kwi1324618970.ps tmp/35kwi1324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/4w9nv1324618970.ps tmp/4w9nv1324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/5cin11324618970.ps tmp/5cin11324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/6x7ao1324618970.ps tmp/6x7ao1324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/7pzvw1324618970.ps tmp/7pzvw1324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/8025k1324618970.ps tmp/8025k1324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/9r9o31324618970.ps tmp/9r9o31324618970.png",intern=TRUE)) character(0) > try(system("convert tmp/10td5z1324618970.ps tmp/10td5z1324618970.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.760 0.641 5.432