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Data X:
366.356 774.414 -4.4 4.2 0 18 19 116 304.452 803.398 -5.7 4.8 -0.3 69.1 9 506 371.357 470.048 -13.5 4.3 0.2 80 3 95 294.444 75.251 1.4 3 0.1 177 22 161 406.044 77.626 4.1 5.6 1.1 287 7 80 368.888 788.683 5.8 2.3 -0.1 200 9 33 33.322 781.521 2.7 1.9 0.4 228 7 129 33.673 777.779 7.1 8.9 0.2 220 15 155 207.944 689.163 4.1 2 0.1 183 9 132 194.591 76.774 1.1 5.2 0.1 43.1 10 480 33.322 571.373 -9 3.4 0 80 6 98 321.888 833.471 1.6 4.4 -0.3 78.1 16 558 109.861 465.396 -0.4 5.7 0.8 267 3 121 53.845 738.895 -4.8 6 0 81 20 122 393.183 781.763 -0.9 1.4 -0.3 236 15 51 33.673 496.981 -0.5 0.6 1.7 341.1 4 552 283.321 780.384 -1 1.8 0 16 7 150 304.452 762.168 -2.3 5.2 -0.1 66.1 12 428 299.573 521.494 5.8 2.6 -0.2 68.8 3 582 421.951 764.204 5.1 2.2 1.1 199 18 538 304.452 777.149 10.8 2.4 -1.5 329.8 13 579 37.612 831.385 12.2 4 -2.8 230.4 17 572 358.352 763.964 -2.8 2.1 -1.6 210.2 11 512 248.491 705.531 11.2 3.3 2.3 302.8 23 604 248.491 738.275 13.6 0.6 -0.8 159.8 11 602 33.322 756.786 -12.3 3.7 -0.2 70 12 460 313.549 792.226 4.2 1.4 0.2 161 7 127 207.944 738.771 -2.8 4.5 0.1 53.3 21 417 368.888 74.793 3.4 7.2 0.5 209.1 12 477 299.573 397.029 -11.7 2.7 1.7 81 4 87 398.898 805.102 -2.5 3.2 0.1 83 9 51 304.452 667.834 3.9 4.8 -0.6 66.8 8 573 355.535 734.601 3 1.4 1 200 21 177 179.176 754.062 0 6.1 -0.2 207.5 19 489 304.452 482.028 -2.6 2.1 0.7 72.8 4 530 256.495 780.057 1 2.2 0 99 7 65 436.945 741.878 -0.2 1.1 3.2 138 22 49 346.574 796.032 7.7 4.8 -0.2 66 17 196 460.517 823.669 10.7 5.3 -0.9 205 17 192 309.104 830.721 9.3 7.3 -0.5 206 17 212 415.888 826.333 9.5 5 -0.9 208 17 208 179.176 750.329 1.6 4.5 0.1 117 19 62 248.491 649.527 -3.4 0.5 1.1 217 6 135 321.888 774.414 -1.3 4.2 -0.2 59 15 149 373.767 675.577 -3.2 2.6 0.6 70.5 21 398 42.485 651.915 -1.8 2.3 1.1 81 23 174 38.712 477.068 -0.5 0.5 0.7 358 4 402 400.733 788.721 7.6 4 -0.6 180 13 208 294.444 542.053 3.4 2.9 0.4 74.7 3 567 309.104 380.666 7.4 3.2 -0.1 225 3 205 194.591 48.752 -3.5 3.8 -0.1 60.5 3 418 352.636 825.088 19.8 4.8 -1.9 260 17 206 38.712 785.516 16.3 3.4 -0.1 225.3 20 605 299.573 825.427 -7.3 5 0 60 8 506 407.754 736.201 -0.6 0.8 1.1 88.3 21 422 321.888 759.388 -0.4 4.5 -0.2 64.6 13 430 349.651 835.208 17.8 5 -2.5 219.6 16 599 32.581 462.497 -1.9 2.2 2.2 268 4 172 299.573 739.879 -10 3.8 -0.1 78.4 20 449 270.805 648.616 -1.3 2.9 0.7 63.3 24 397 309.104 620.456 4.7 1.5 1.1 104.4 1 588 406.044 764.348 0.3 1.5 -0.3 172 13 130 361.092 759.337 8.8 2.2 0 186 21 577 256.495 643.455 -9.3 3.6 0.1 71.2 9 450 160.944 700.033 -2.4 5.8 0 61 22 418 50.876 749.499 2.9 1.2 2.1 271.1 21 543 230.259 780.221 2.5 5 0.1 135 7 128 32.581 755.276 13.4 3.9 0.3 216.8 19 606 366.356 682.979 -15.5 3.1 0.2 70.3 22 460 304.452 749.053 -1.6 2.2 -0.9 211.7 12 501 34.012 759.035 0.1 2.6 -0.1 73 11 66 304.452 551.745 -2.8 0.5 2.2 5 5 155 34.012 818.619 -0.9 1.3 0.6 57 8 67 355.535 595.842 -10.3 1.2 2.5 86 24 86 397.029 755.276 -4.1 0.7 -0.7 264.8 13 401 472.739 777.022 -3.8 4.9 -0.2 68 7 166 430.407 799.834 8.2 5.6 -0.6 210 15 212 256.495 715.305 -4.8 4.7 -0.1 74.6 23 441 378.419 795.997 -4.3 6 0.1 18 13 82 495.583 657.508 6.2 1.3 1.1 226 24 200 366.356 788.231 3.3 5.8 -0.1 46.9 19 557 526.786 743.603 -1 1.8 1.4 89 20 44 346.574 495.583 -4 1.7 1 65 2 165 207.944 51.299 7.8 1.6 1.7 184.3 4 604 33.673 720.638 -5.3 1.8 -0.2 80 13 451 329.584 746.107 2.2 3.1 0.1 62.3 13 470 219.722 753.209 14.8 4.2 -4.5 227.7 11 588 343.399 813.359 -4.8 1.5 0 196 17 100 32.581 691.771 12.8 1 0.3 103.5 24 602 283.321 712.206 -3.2 4.6 -0.1 62.2 12 427 363.759 82.845 0.7 0.8 -0.8 86 8 541 270.805 756.528 3.5 6.9 0.2 204.4 15 482 299.573 765.112 -6.8 2.2 -0.4 78.8 16 517 400.733 767.183 8.3 0.7 -1.3 206.2 14 532 343.399 631.173 -19 2.3 0.8 60.9 8 461 0.69315 70.775 7 4 -0.2 54.3 10 578 352.636 734.148 -14.6 1.6 -0.4 228.9 14 457 263.906 796.346 3.6 3.2 1.2 268 18 42 194.591 735.116 3.5 1.9 0.2 215 20 107 371.357 754.115 5.2 0.9 -1 280 11 155 283.321 664.249 -8.3 2.6 0.2 60 23 85 343.399 756.579 0.6 3.8 -0.4 64.6 12 507 329.584 81.806 -0.5 0.7 -0.2 248 15 124 317.805 760.738 1 2.4 -0.1 192 13 38 481.218 754.327 -8 0.6 0.5 88 13 94 463.473 820.985 -3 1.5 2.7 89.6 8 470 304.452 576.205 5 3.2 0 58 6 195 38.712 691.274 -5.1 0.8 1.4 241 23 137 368.888 819.781 0.2 2.4 0.5 80 8 72 433.073 76.024 12.9 5.6 -0.8 46 13 188 461.512 754.327 2.6 2.6 -1.9 243 11 45 443.082 770.661 7.8 8 -1.2 33.7 13 556 34.012 554.518 -0.7 2 -0.3 254 1 542 248.491 768.432 7.7 1.5 -0.1 89 16 209 329.584 790.064 1.5 1.3 0.9 334.7 18 422 294.444 776.684 15.8 3.2 -0.2 125.5 17 595 33.673 797.797 4.3 5.7 -1 232 9 156 289.037 789.767 8.1 6.4 -0.5 199.4 7 577 490.527 824.065 11.6 6 -1.3 213 16 193 263.906 707.581 2.8 3.2 0.3 223 10 69 329.584 77.424 -4.4 4.9 -0.1 23 10 82 371.357 697.915 -5.1 3.3 1.4 81 23 98 439.445 827.741 2 2.5 -0.3 207.2 16 536 382.864 801.268 10 4.8 -0.5 83.2 9 600 256.495 578.996 1.1 4 -0.1 79 3 70 33.322 745.934 6.1 2.5 0 92 22 210 313.549 622.851 0.1 1.9 1.1 208.8 6 538 0.69315 645.362 -2.6 4.9 0.2 38.3 23 405 400.733 77.178 7.9 0.4 0.5 276 19 184 32.581 792.696 4.8 9.4 0.6 204 14 474 32.581 656.244 2.6 2.8 -0.7 224.1 8 545 484.419 817.273 -9.6 1.1 1.3 191 16 94 263.906 51.299 -1.5 2.5 -0.1 245.1 4 510 138.629 454.329 3.8 5.8 0.7 201.9 3 473 32.581 571.043 1.8 2.7 0.9 181.9 1 527 230.259 819.257 -0.7 4.1 0.6 252 8 121 309.104 500.395 3.6 2.7 1.2 344.7 4 533 294.444 739.817 3.9 6.2 0.7 206 20 155 34.012 663.988 4.7 3.6 0 59 24 196 299.573 629.342 -2.5 4.9 -0.2 84 7 167 382.864 74.378 -9.9 4.5 -0.1 55 11 89 230.259 77.977 1.7 2 0.3 38 15 63 429.046 733.629 -12.8 3.5 0 79 19 97 441.884 751.589 4.3 2.1 0.6 32.3 20 555 33.673 770.841 2.1 3.1 0 79 10 64 230.259 464.439 -2.2 4.9 -0.1 77 2 114 398.898 777.402 3.3 1.8 -0.3 220 10 155 412.713 505.625 5.6 3.5 -0.1 78 4 184 368.888 586.363 -0.6 0.6 1.7 142 1 79 230.259 552.943 3.4 4.7 0.8 220.1 5 474 329.584 791.754 0.2 2.8 0.4 335 15 53 313.549 674.052 -6.4 2.8 -0.1 77 22 84 207.944 653.669 8 1.9 -0.2 54.6 8 578 525.227 782.844 3.6 0.8 1.5 87.7 19 529 378.419 774.846 -13.4 4 0.2 74.1 13 448 397.029 571.043 -2.1 1.3 1.8 87.8 1 485 299.573 564.897 -8.7 4.3 -0.2 74.5 1 450 256.495 642.972 1.6 1.3 1 58 8 76 321.888 651.323 -3.9 2.8 0.4 71.3 8 398 138.629 793.057 1.4 2.5 0.2 210.5 19 525 313.549 759.337 3.3 4.2 1.2 235 20 138 406.044 719.818 3 1.8 1.1 191 22 192 427.667 823.377 7.2 3.8 -0.2 31 15 173 349.651 813.212 -1.7 1.5 -0.1 68 8 515 321.888 787.284 0.8 5 0.1 76.2 19 514 407.754 753.102 0.1 3.5 1.2 66.3 20 397 420.469 749.276 4.5 6.6 -0.1 210 12 156 418.965 565.599 0.3 1.5 1.7 303.4 1 529 248.491 707.327 -0.9 1.6 -0.5 256.5 9 510 109.861 633.683 2.2 2.8 0.1 142 1 63 248.491 721.229 -0.6 2.1 0.1 60 21 134 248.491 786.978 3.2 2.6 1.3 286 20 42 0.69315 784.031 4.1 2.7 0.2 175 19 56 434.381 798.344 -4.8 0.8 1.1 230.1 17 445 263.906 703.086 7.1 1.6 0.5 66.4 22 593 329.584 790.175 -4.4 3.8 0.1 15 9 82 417.439 772.223 7.1 3.9 -0.9 90 10 197 371.357 819.451 0 0.8 -0.3 254.2 16 500 402.535 784.698 11.6 4.2 -2.7 247 14 200 485.203 758.731 3.1 2.2 -3.4 227 11 148 464.439 647.235 1.5 1.2 1.3 101 24 191 363.759 774.932 15 7.3 -2.2 229.9 14 584 34.012 812.711 3.6 4.9 1.2 238 18 138 179.176 568.358 5.7 1.9 0.3 49 6 189 411.087 758.274 3.4 6.9 -0.1 194.9 11 548 33.673 801.434 10.1 2.4 -0.3 44 17 189 444.265 765.539 -2.4 2.6 0.7 78.3 18 398 277.259 783.716 0.2 4.5 0 80 7 157 371.357 69.921 -15 3.3 0.6 66 23 462 517.048 808.209 5.2 7.2 -1.3 202.7 14 537 309.104 785.554 4.1 3.4 0.1 79 7 170 270.805 768.064 6.3 9.4 0.2 248 16 160 411.087 75.438 8.7 4 -1.2 216.3 14 538 479.579 830.598 2.4 4.2 -0.7 65.1 8 556 23.979 595.324 -5.3 1 2.2 60 9 77 299.573 62.634 2.5 4.3 -0.1 79 24 69 313.549 825.036 9.3 5.4 -0.8 213 16 212 343.399 761.776 -5.6 3.1 -0.5 77.4 11 519 34.012 744.425 5.6 7 1 248.1 12 471 309.104 787.169 -1.7 0.5 0 218 18 51 445.435 764.492 -5.6 4.9 -0.1 56.7 7 409 418.965 746.851 -3.5 0.7 0.2 165.1 20 520 373.767 818.256 -11.2 3.7 0.2 78 16 96 420.469 510.595 -11.9 0.6 0.8 286.5 4 489 256.495 579.301 2.1 2.6 3.1 241 1 32 256.495 714.125 1 4.5 1.3 232 21 145 485.981 769.303 8.8 3.6 -2.5 85.4 12 547 525.227 723.056 -4.6 6.5 0.1 80 21 122 263.906 60.845 -5.8 2 -0.3 107.5 1 518 313.549 572.031 1 1.8 0.6 92 3 76 194.591 681.892 0.1 1.7 -0.1 214 11 112 34.012 567.332 -1.9 0.9 3.7 109.2 5 397 472.739 826.178 1 3.4 1.3 248 8 43 33.673 592.959 2.1 3.8 0.5 64.2 1 531 32.581 753.262 6.1 2.5 -0.1 182.5 21 572 373.767 811.761 0.2 0.8 0.9 11 16 113 179.176 798.446 1.9 5.8 0.2 9 9 80 406.044 77.463 11.8 6 -0.7 212.7 14 582 391.202 819.229 -4.4 1.5 0.5 87.9 8 423 0.69315 643.294 1.9 2.4 0.1 133 24 62 160.944 52.832 8.6 1.8 1.5 242 3 34 446.591 822.336 9.1 9.4 -0.5 39.4 16 556 317.805 768.983 13 0.3 0.4 114 22 602 289.037 670.564 1.8 0.8 0.1 269 6 141 417.439 758.426 4 3.1 -1.7 103.7 12 554 373.767 804.943 -7.8 0.6 -0.1 177 17 95 400.733 772.886 8.7 5.5 -0.4 132.3 14 573 304.452 751.806 -4.9 4.1 -0.2 73.8 13 436 263.906 758.172 -8.8 8.1 -0.1 53 18 90 411.087 828.425 2.9 3.3 0.8 22.1 17 397 447.734 801.731 0.4 3.9 0.7 67.4 18 507 317.805 767.786 -0.7 4.3 -0.4 59 13 151 33.322 78.598 4.2 2.7 1.1 230.7 18 526 0.69315 479.579 2.7 2.8 0.2 187 4 131 458.497 766.528 7.4 0.9 -0.2 55 13 184 0.69315 436.945 0.6 4.6 0.1 350 3 171 34.012 75.251 6 3.5 -0.2 78.1 21 571 207.944 773.849 1.6 1.6 0.3 211.3 21 525 455.388 762.071 3.4 5.9 -0.6 45 13 164 321.888 539.363 3.3 1.7 -0.1 187 4 202 277.259 587.774 -5.4 5.1 -0.2 72.2 2 441 329.584 58.522 4.2 1.7 1 175 5 587 33.322 802.027 2 6 -0.1 152 18 61 402.535 723.706 -14.2 1.4 -0.1 238.1 18 457 438.203 783.281 9.4 2.9 -0.3 248.4 15 540 299.573 460.517 1.5 1.1 0.2 233.7 3 480 355.535 811.073 0.6 6.8 0.3 10 8 54 32.581 757.917 2.5 3 -0.2 83 13 64 447.734 831.361 -0.3 3 -0.8 71.8 8 554 406.044 486.753 1.4 0.7 1.5 79.4 4 563 321.888 750.879 -0.7 4 -0.5 65.1 11 507 446.591 651.323 -8.1 0.7 1.2 111 24 143 313.549 66.107 -13.1 3.5 0 83 9 97 230.259 470.048 6.3 6 0.9 219.2 2 586 361.092 694.986 -3.8 0.7 -0.2 258 23 74 313.549 572.685 -3.6 0.8 4 302.4 5 470 389.182 816.337 -1.1 1.5 -0.2 157.4 16 521 321.888 77.012 15.8 3.9 -0.4 119.5 15 595 317.805 445.435 -5.1 3.4 0.4 58.4 3 507 373.767 828.248 8.5 3.1 -0.7 238 8 205 23.979 805.833 -2.1 4.1 -0.2 82 8 114 368.888 790.027 1.5 0.5 -0.6 99.2 13 509 426.268 734.148 3 0.8 0.6 86 21 32 494.164 790.027 -12.6 2.2 0.2 77.8 19 488 329.584 765.917 3 3.1 -0.1 221 14 169 207.944 560.947 -5.2 2.9 0.1 60 2 90 219.722 715.227 3.5 0.9 0.2 265 22 169 207.944 542.495 2.8 1.3 0 75.8 2 404 454.329 78.071 6.5 4.3 -1.1 44 11 173 207.944 794.839 2.5 3.6 -0.1 54.7 16 574 436.945 834.069 6.3 4.2 -0.1 76 16 166 397.029 754.062 -1.4 1.7 -0.2 86 12 51 398.898 589.164 1.7 1.1 2.4 173.1 1 533 299.573 752.402 2.4 7.9 -0.1 43.5 21 557 352.636 643.294 -0.1 1.6 -0.2 75 22 55 299.573 750.219 3.1 1.7 0.3 269 12 69 539.363 804.045 12.9 8.3 -1.1 357.5 14 551 363.759 731.986 -13.4 3.8 0.1 75 11 448 230.259 543.372 0.7 3.9 0.1 182.9 2 491 492.725 794.058 2.4 1 0.4 110.7 7 533 294.444 817.808 -1.3 5.6 -0.2 46 17 149 270.805 765.728 -6.3 4 -0.1 51.6 19 408 207.944 756.164 3.5 1.8 0 71.2 21 576 34.012 798.752 0 4 -0.3 78.5 9 430 505.625 763.143 11.8 2.4 -1.5 232.5 14 535 493.447 763.192 5.8 1.9 -3.1 260.8 12 541 256.495 76.324 3.1 4.7 -0.1 48 12 576 304.452 79.248 1.4 2.1 0 221 17 525 138.629 430.407 0.8 3.1 1.6 77 3 50 277.259 767.555 6.8 9.9 -0.2 249 15 160 391.202 71.025 1.3 8 0 61.6 23 557 435.671 795.437 6.8 1.5 -0.6 124.9 7 585 34.012 787.474 -6.8 1 0 207 15 84 402.535 785.166 10.5 4.4 -0.9 69 15 198 373.767 826.049 3.8 5.2 0 222 8 163 294.444 77.411 -12.8 3.6 0.1 68.4 14 460 409.434 524.702 1.3 0.8 1.1 72.3 5 563 304.452 524.175 -4.2 1.4 3.6 230 2 155 317.805 755.224 -0.6 2.5 -0.1 75 13 111 256.495 796.242 -6.1 5.2 0.4 27 18 82 263.906 685.751 5.1 5.5 0.1 230 10 126 309.104 81.191 0.8 3 -0.1 78 17 65 34.012 800.068 -4.4 3.7 -0.1 78 14 68 219.722 411.087 -6.5 2.1 -0.1 68.2 5 451 37.612 481.218 -3.7 0.9 -0.1 281.3 4 513 277.259 642.811 0.7 2.9 1.4 229.6 24 473 34.012 495.583 -5.7 3.3 0.6 72 2 401 361.092 616.121 8.4 3.3 0.7 80.5 24 564 33.673 655.251 -0.2 2.8 0.7 71 23 72 0.69315 51.299 -1.9 4.5 0.4 17 2 40 294.444 518.739 -7.3 1.9 0.5 85 3 118 417.439 791.608 0.1 2.1 2 77 18 49 283.321 733.954 -5.9 2.9 0.2 64.6 22 406 304.452 70.076 4.7 5.6 0 69 23 211 32.581 787.664 4.2 4.4 0.6 189.8 15 472 321.888 723.778 2.1 5.4 0.1 159 21 61 423.411 764.348 -0.5 2.1 -2 247.8 14 513 481.218 708.339 -3.7 1.1 0.1 192 22 101 439.445 795.718 6.5 6.2 -0.1 210.8 18 547 263.906 642.162 2.1 4.1 0.7 260 24 43 32.581 729.029 -3.1 1 -0.2 211 21 102 194.591 542.495 -12.8 0.8 1.2 55 6 91 294.444 729.029 3.8 4.3 0.5 210 22 105 256.495 752.348 3.4 6 0.2 191 14 482 321.888 563.479 -4.2 2.1 1.1 91 2 68 277.259 797.694 -1.7 5.2 0 76 8 124 461.512 778.197 5.4 3.6 -1.1 44 10 173 160.944 5.743 3.4 4.9 0.7 243 2 140 207.944 5.743 -0.2 5.6 0.2 16.6 2 553 38.712 562.762 2.1 1.5 2 227.8 5 533 317.805 785.477 -12.5 3.2 0.2 82.1 15 456 358.352 756.941 -4.1 4.3 -0.1 44.7 14 409 468.213 708.087 -9.8 0.5 0.2 131 21 83 256.495 743.603 -4.9 4.7 -0.1 79.6 21 441 230.259 611.368 -5.2 3.5 0 59 1 90 355.535 797.488 -1.6 3.5 0.5 34.5 18 480 346.574 669.084 6.4 1.2 0 188 6 207 248.491 779.523 2 2.8 1.6 242 18 127 421.951 521.494 -8.5 1.5 2.8 279 10 93 230.259 765.112 3.6 7.6 0.5 199.3 17 482 270.805 612.905 0.4 0.8 0.1 297 7 524 299.573 808.979 1.2 3.6 0.1 63.9 15 411 248.491 576.519 -3.5 3.2 0 240.2 2 504 313.549 806.401 3.6 2.3 -0.3 9.4 9 549 415.888 739.265 -14.9 1.9 0.8 65 20 91 179.176 643.294 1 2.5 -0.2 75 10 70 329.584 762.462 -1.7 1.6 -0.1 172 19 51 283.321 522.036 3.4 1.1 1.4 89 6 565 352.636 635.611 6.9 7 0.8 220 24 34 32.581 447.734 -4.8 2.5 0.4 84 3 101 398.898 650.279 4.2 3.9 0.6 78 24 197 160.944 688.959 1.5 4 0.1 240.4 22 523 349.651 732.909 -2.9 1.9 1.7 337.8 19 468 317.805 73.601 -8.2 4.7 -0.2 76.5 11 408 467.283 777.107 7 3.1 -0.3 73 10 185 343.399 616.121 8.1 1.9 -0.1 211.9 1 578 207.944 797.281 3.7 4.2 0.2 172 9 128 329.584 790.323 0.7 2.1 1.3 207.1 18 473 230.259 816.223 0.4 8.6 0.1 34 17 39 207.944 483.628 -10.4 1.9 1.1 75 7 86 0.69315 491.998 6.5 4.5 0.4 206 2 57 313.549 747.591 9 4.6 -0.9 208.7 10 587 382.864 752.941 10.1 1.1 -3.1 255 11 188 38.712 788.796 -0.3 1.7 0.4 26.9 15 416 299.573 447.734 -4.4 2.6 0.8 85 4 38 32.581 773.281 1.7 1.5 1.1 345 19 158 33.322 693.245 -3.2 0.8 -0.1 260 22 68 349.651 765.634 -5.9 3.1 -0.1 77 16 85 194.591 70.193 3.7 3.6 0.1 195 22 107 457.471 80.762 9.9 2.2 0 92 16 177 391.202 790.175 7.4 4.3 -0.3 178 18 190 380.666 689.669 5.1 2.5 0.7 80 23 197 393.183 430.407 3.2 1.5 0.4 75 3 194 248.491 515.906 0 4.3 0.1 102.7 3 477 313.549 782.764 -5.6 6.1 -0.2 79.5 17 441 294.444 702.554 0.7 2.4 -0.2 232.5 23 542 34.012 790.175 15.1 2.9 0.2 113.9 19 567 194.591 573.334 -2.2 4.3 -0.1 72 5 124 317.805 534.711 -3.8 2.7 -0.2 80.5 3 511 321.888 758.477 4.2 6.5 0.4 214.3 11 474 263.906 684.055 -13.1 4.8 -0.2 52.8 11 462 33.322 755.381 -0.2 3.9 -0.2 79.6 12 430 270.805 478.749 1.5 3.2 0.1 153 4 61 378.419 686.485 0.8 1.5 -0.1 231.5 23 540 378.419 781.197 -6.6 2.2 1.3 87 7 122 160.944 789.469 2.1 4 -0.1 47.8 14 574 33.673 776.132 1.7 2.9 -0.1 81 14 60 304.452 607.764 -4.1 5.4 -0.1 66.5 1 427 445.435 780.954 18.2 3.7 -2.7 250.7 15 568 194.591 54.848 2.2 2 1.9 253.8 5 473 263.906 527.811 -7.8 4.6 -0.1 71.5 19 450 33.322 776.684 -5.4 3 -0.2 77 14 85 343.399 55.835 -4.5 4.1 0.3 59.4 1 507 389.182 786.634 8 6.1 0.1 197 19 212 219.722 819.644 2.7 3.8 0.2 139 8 128 459.512 759.186 -5.6 3.9 -0.2 41 13 116 349.651 554.126 4.6 0.9 0.5 108 5 190 283.321 755.799 12 4.4 0.2 274.2 20 584 219.722 651.471 4.4 2 0.7 205 6 33 289.037 621.461 4.5 3.5 0 55 9 196 34.012 663.988 0.2 0.5 1.4 84.8 24 483 299.573 602.345 -18.6 2.3 0.1 79.4 7 457 373.767 762.413 0.1 2.6 1.5 230 19 175 294.444 584.064 7.4 4.3 0.3 189.6 1 590 358.352 832.579 7.6 4.2 0 224.1 8 583 329.584 732.053 8.6 2.6 -0.1 189.2 22 577 48.752 791.571 -2.5 3.6 0 64 15 143 433.073 77.424 10.6 1.8 -1.6 245 14 177 329.584 691.771 -1.6 1.1 0 282 23 51 378.419 778.239 5 3.1 -0.4 230 16 545 361.092 518.739 5.2 4.4 0.8 206 4 126 283.321 614.204 5.3 2.3 1.2 153.1 1 587 37.612 548.064 -13.1 1.1 1.3 62.9 5 464 358.352 52.933 3.3 2.2 0.5 77.1 2 562 317.805 54.848 -0.8 3.5 0 176.8 5 522 352.636 503.044 -4 1.5 -0.1 108.2 2 521 421.951 76.406 1.7 2.3 -0.3 85 15 167 393.183 829.255 6.1 4.2 0.3 23 17 173 230.259 570.378 5.8 2.8 0 43 7 189 32.581 54.848 5.7 3.3 0.5 228 5 204 270.805 702.997 14.9 2.8 -5 255.5 10 594 355.535 531.321 -5.7 2.2 0.6 82 5 165 194.591 614.419 0.2 3.1 0.1 73 9 56 436.945 514.749 -9 1.3 0.4 77 2 88 470.048 766.388 16.8 6 -1.1 272 14 205 248.491 58.944 2.8 4.7 0 66 2 574 160.944 761.085 -0.1 6.6 -0.3 205.2 14 489 378.419 752.294 -12.5 0.8 -0.4 232 19 463 194.591 482.831 -7.8 3.7 0.1 58.4 4 407 309.104 754.908 0.9 1 -0.6 213.1 12 484 321.888 775.833 -4.2 4.6 -0.1 78 10 120 248.491 750.659 21.9 3.6 -2.5 264.1 19 608 219.722 607.764 -10.1 2.8 0 73 1 89 493.447 701.571 -9.4 1.2 0 73.8 23 437 404.305 759.488 11.2 1.7 -2 236 12 188 451.086 820.576 1.8 3.2 0.2 216.6 8 551 194.591 459.512 0.5 5.5 0.1 354 4 171 309.104 823.297 -2.2 1.6 -0.3 211.7 16 501 460.517 831.532 -0.1 5.2 -0.8 79 8 555 363.759 757.096 8.4 5.4 -1.8 240 11 163 346.574 761.036 0.9 3 -0.7 340 12 142 38.712 821.528 -2.9 1.4 -0.2 113.4 8 521 515.329 819.146 2.3 2.5 0.6 16 17 44 304.452 767.322 -1.4 4.4 -0.1 38.1 14 410 349.651 778.655 0.4 1.5 -0.1 110 13 124 256.495 469.135 -11.3 2.5 1.2 82 5 87 385.015 7.629 0.1 3.9 -0.2 70.7 14 506 248.491 549.717 -5 4 -0.1 75.4 5 440 207.944 657.368 1.6 2 1.2 212.7 6 472 299.573 790.618 -2.8 2.3 -0.1 205 20 511 138.629 655.251 -3.5 3.9 -0.1 46.3 24 409 317.805 822.013 2 3.5 -0.2 82 8 64 219.722 542.935 2.4 3.6 0.1 125 5 128 355.535 789.096 7.1 3.4 -0.3 82.5 19 571 38.712 802.453 -2.7 1.4 1.6 66 9 73 34.012 714.283 -1.3 1.2 0.6 66 21 113 304.452 797.039 5.5 3.9 -0.5 231 14 131 434.381 665.801 5.5 1.1 0.9 138 24 199 23.979 710.003 -4 5.8 -0.4 78.4 11 399 263.906 765.681 -0.2 2.4 0 41 19 157 256.495 470.953 -2.8 1.8 1.4 198.9 3 537 33.322 560.212 3.8 3.9 -0.2 85 5 187 256.495 785.127 0.2 2.8 0.1 78 17 112 368.888 789.655 12.8 6.8 -0.6 227.7 15 583 23.979 720.638 -0.8 1.6 1.7 192.6 22 469 23.979 489.035 -10.8 1.5 0.2 57 3 460 468.213 756.735 -10.2 0.6 2.4 110.8 10 465 304.452 761.135 0.8 3.1 -0.1 65.6 19 429 304.452 666.823 4.1 1.4 0.2 139.8 24 572 219.722 50.689 4.3 4.9 0.1 82 2 212 317.805 746.107 -2.8 1.4 -0.1 243 20 102 448.864 768.018 -0.4 0.8 2.6 147 21 49 230.259 780.344 2.4 3.9 0.2 14.3 20 574 329.584 826.256 3.4 0.9 0.3 228 16 109 317.805 76.695 12.1 2.8 -3.2 256 13 203 406.044 533.272 -2.5 2 1.3 80.7 3 532 415.888 630.992 -4.5 2 0.3 90 24 100 309.104 667.456 2.2 7.1 0.1 37.9 6 557 441.884 809.316 -4.7 1.4 1.2 276.8 18 445 289.037 656.667 0.1 2.1 -0.2 247.4 6 543 109.861 583.481 -5.8 7.7 0.1 47 7 90 343.399 7.794 3.3 4.3 0.8 217 17 105 352.636 776.089 2 1.7 1.1 234 15 121 313.549 767.276 1.3 4.2 0.2 169 10 61 219.722 7.979 1.4 5 -0.1 40.7 9 480 313.549 778.406 6.1 1.9 0.4 171 21 210 207.944 595.842 -3.1 4.2 -0.1 52.5 2 426 363.759 454.329 -11.5 1.7 3.7 90.4 4 465 373.767 562.762 -6.6 1 -0.1 200 2 445 248.491 566.643 -3.8 2.1 0.6 73 3 77 194.591 754.539 6.5 9.4 -0.9 250 11 160 194.591 623.832 -0.4 3.3 0.3 215.1 24 470 277.259 456.435 -6.3 2 2.3 223 3 148 270.805 658.203 2.2 1.8 0.1 64.2 6 549 179.176 531.321 -4.9 4.2 0.3 353 2 117 230.259 561.677 -1.3 2.8 -0.1 65.2 1 486 411.087 77.111 -5.1 0.7 0.3 60 10 99 34.012 62.519 0.1 1 0.2 87 24 111 368.888 785.516 6.5 5.2 -0.2 69 19 196 417.439 824.512 8.6 1.6 -1 258.8 15 530
Names of X columns:
PartikelsFijnstof AutosPerUur TempOp2mHoogte Windsnelheid TempverschilTussen2mEn25m Windrichting Uur Dag
Sample Range:
(leave blank to include all observations)
From:
To:
Column Number of Endogenous Series
(?)
Fixed Seasonal Effects
Do not include Seasonal Dummies
Do not include Seasonal Dummies
Include Seasonal Dummies
Type of Equation
No Linear Trend
No Linear Trend
Linear Trend
First Differences
Seasonal Differences (s)
First and Seasonal Differences (s)
Degree of Predetermination (lagged endogenous variables)
Degree of Seasonal Predetermination
Seasonality
12
1
2
3
4
5
6
7
8
9
10
11
12
Chart options
R Code
library(lattice) library(lmtest) 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 k <- length(x[1,]) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) 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)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } bitmap(file='test0.png') plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() bitmap(file='test1.png') plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() bitmap(file='test2.png') hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() bitmap(file='test3.png') densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() bitmap(file='test4.png') qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') qqline(mysum$resid) grid() dev.off() (myerror <- as.ts(mysum$resid)) bitmap(file='test5.png') dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) z 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() bitmap(file='test6.png') acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() bitmap(file='test7.png') pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() bitmap(file='test8.png') opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { bitmap(file='test9.png') plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } load(file='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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT<br />H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a, sqrt(mysum$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$sigma) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a, sum(myerror*myerror)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE) a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]-mysum$resid[i]) a<-table.element(a,mysum$resid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable4.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='mytable5.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='mytable6.tab') }
Compute
Summary of computational transaction
Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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