Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
8485 24 13 1 1500000 0 0 0 103833 10 6 1 15000 4 0 1 9964 45 0 0 10000 2 1 1 15000 4 3 1 18896 9 6 1 5000 3 0 1 30657 10 0 0 20335 7 5 1 3105 40 1 1 34965 5 1 0 25302 4 0 0 7400 8 2 1 17232 6 6 1 13681 1 1 1 16000 2 0 0 10879 0 0 0 36000 3 0 1 434084 44 7 1 33837 5 4 1 3370 0 1 1 12101 14 4 1 11242 37 0 0 90215 3 4 1 326 4 1 0 228 0 1 0 14034 8 0 1 37700 11 5 1 18491 6 0 1 12913 4 3 1 100000 26 2 1 0 0 0 1 3500 37 0 0 600 5 3 1 0 0 0 1 17859 4 0 0 50 39 0 0 52000 8 1 1 0 0 0 1 31730 3 0 0 7551 5 4 1 0 5 0 1 17000 45 0 0 12000 2 0 1 0 0 0 1 52000 15 0 0 0 5 0 0 1126 4 4 1 39466 7 0 0 113 0 0 0 21000 7 0 0 0 0 0 0 27368 19 5 1 20200 1 20 1 50000 3 4 1 18450 4 1 1 9520 57 0 0 8241 4 1 1 101647 47 10 1 37782 8 3 1 25109 42 0 0 46500 0 1 0 0 52 0 0 16112 5 4 1 80000 5 4 1 526269 29 16 1 70745 5 5 1 20516 10 0 1 400 10 1 1 24000 7 1 1 20000 79 0 0 1025 38 0 0 70000 5 4 1 0 0 0 1 3084506 43 0 1 9206 3 1 1 10882 60 0 0 29828 7 2 1 1000 79 0 0 0 0 0 0 18269 8 0 0 710 3 0 0 32031 4 6 1 68770 9 16 1 12759 4 1 1 10659 9 1 1 7495 2 3 0 19951 0 1 0 6333 2 1 0 2056743 26 35 1 73467 40 0 0 16000 35 2 1 10393 79 0 0 0 0 0 0 2662 5 4 1 23300 0 1 0 0 10 0 0 0 10 3 1 25986 2 8 1 6541 4 4 1 0 0 0 1 9964 44 0 0 6971 41 0 0 6986 43 1 1 0 0 0 1 5000 6 1 1 9501 5 1 1 3152 55 0 0 23009 11 9 1 68120 3 1 1 61092 0 1 1 9841 5 2 1 10000 76 0 0 0 0 0 0 41214 0 0 0 377 2 1 0 2000 20 3 1 10000 0 1 1 28467 15 0 0 12545 5 8 1 12500 18 0 2 5000 20 0 2 2188 6 5 1 25000 23 0 0 250 0 0 0 18127 0 1 1 5256 14 1 1 37000 12 0 0 18013 3 2 1 17504 0 1 1 2803 6 4 1 28074 17 1 1 637957 47 0 0 12804 32 0 0 10000 0 0 0 27607 0 1 0 18736 0 1 0 337 3 2 0 15869 0 0 2 0 4 0 2 4123 2 3 1 85291 0 1 1 16340 6 1 1 9133 1 1 1 2676 8 3 1 0 0 0 1 14634 5 1 1 0 5 0 0 10000 3 1 1 3030 9 1 1 9695 45 0 0 4000 8 2 1 2960 5 2 1 54938 4 0 1 634746 47 22 0 7164 10 4 1 100 32 0 0 1451529 46 25 1 55000 5 0 1 23747 5 6 1 4200 9 7 1 127800 34 10 1 53779 0 2 0 3000 3 1 0 9573 38 0 0 16897 0 0 0 500 2 0 0 15463 30 0 0 13650 3 0 0 20833 70 0 0 0 0 0 0 22376 5 2 1 26253 4 3 1 107441 22 7 1 16725 54 0 0 0 0 0 0 66711 3 6 1 517 3 0 1 13986 50 0 0 0 0 0 0 18352 50 0 0 0 0 0 0 70000 15 0 0 1100 9 3 1 59343 5 8 1 14548 40 0 0 7214 5 6 1 78780 7 3 1 20400 5 3 1 0 0 0 1 11492 6 6 1 2998 24 1 1 37240 0 0 1 8240 3 2 1 11322 45 0 0 716360 45 25 1 26059 6 14 1 9666 5 0 1 10000 44 0 0 33100 4 0 1 24573 50 1 1 4700 30 1 1 50400 30 0 0 0 0 0 0 25217 10 1 1 22692 3 2 2 1921 7 10 1 33000 50 0 0 0 0 0 0 5000 7 0 1 80000 7 12 1 0 0 0 1 2000 79 0 0 0 0 0 0 46297 55 0 0 9964 45 0 0 4435 2 3 1 104600 14 29 1 9950 17 0 0 30000 3 1 2 5000 0 1 2 15000 7 5 1 179895 30 9 1 14164 10 6 1 6620 11 1 1 15000 7 5 1 25150 5 2 1 8537 5 5 1 50 4 0 0 14768 0 1 1 9187 0 1 1 176 15 0 1 21507 0 1 1 3643 4 3 1 68350 6 9 1 13671 7 9 1 26771 3 3 1 30540 3 5 1 3811 6 5 1 111680 4 0 2 22465 3 0 2 0 0 0 2 59450 19 0 0 10760 7 2 1 19739 6 2 1 300 28 0 0 15626 4 4 1 30000 5 0 0 8000 10 0 1 41691 3 2 1 1301 8 2 1 19082 9 4 1 10339 6 1 1 149066 13 1 1 206278 10 10 1 14879 9 5 1 23609 60 0 0 0 0 0 0 99014 30 5 1 20000 12 1 1 57675 3 4 1 9517 4 1 1 275000 0 0 0 20000 30 1 0 91500 7 6 1 40810 2 9 1 12150 9 4 1 4489 0 3 1 13067 0 0 0 0 15 0 0 2375691 65 108 1 800 20 1 1 6743 8 2 1 6200 22 0 2 11332 4 2 1 14795 6 7 1 220000 24 13 1 13000 10 2 2 5000 3 0 2 19940 9 3 1 10000 9 2 1 78320 0 1 2 350 4 0 2 13618 10 8 1 0 0 0 1 60000 8 7 1 7000 3 1 2 2000 0 0 2 8510 8 4 1 839804 48 24 1 24000 11 4 1 18782 9 9 1 0 0 0 1 5590 27 2 1 206514 10 7 1 9862 9 1 0 14051 30 0 0 8275 2 17 1 18155 3 0 0 0 6 0 1 93288 9 5 1 0 0 0 1 10000 25 0 0 81400 0 0 2 6350 1 1 2 20624 6 2 1 37538 5 8 1 9200 70 0 0 0 0 0 0 9700 5 2 1 1600 36 0 0 28756 6 1 1 10783 79 0 0 0 0 0 0 43292 5 0 0 142729 4 6 1 0 0 0 1 6000 8 0 1 1000 26 0 0 9233 5 2 0 0 2 0 0 16483 37 0 0 2288 5 2 1 13746 7 4 1 3331 4 5 1 400 21 0 0 10200 4 4 1 11720 3 4 1 0 0 0 1 38000 0 0 2 38000 4 1 2 12580 44 0 0 83198 5 2 1 21000 4 10 1 15383 0 0 2 2078 7 1 2 23709 3 0 0 300000 80 0 0 0 0 0 0 200 5 0 1 13533 4 5 1 120779 7 1 1 153250 26 9 1 20000 0 0 0 16166 3 0 0 565 1 0 0 20000 0 0 0 10000 4 0 0 813950 48 32 1 11943 8 4 1 5000 20 0 0 204508 25 7 1 14600 24 0 0 44638 7 12 1 30300 17 0 0 20000 0 0 0 11491 5 4 1 0 0 0 1 11742 3 2 0 3100 6 3 0 16854 2 3 1 47030 22 1 1 20000 10 6 1 104000 0 7 2 30000 5 1 2 15000 0 0 2 10100 2 0 2 2712 9 0 1 7783 10 2 1 16873 20 0 0 1286082 49 24 1 61190 10 6 1 556585 4 12 1 28617 10 6 1 600000 51 10 1 39792 9 4 1 9329 7 3 1 150000 14 4 1 10500 3 1 1 12873 3 8 1 25000 2 0 0 24600 2 5 0 6913 2 5 1 248307 23 6 1 1500 2 5 1 28932 2 3 1 293015 20 6 1 0 0 0 1 102426 15 11 1 46649 5 3 2 7193 7 0 2 16063 6 8 1 0 0 0 1 57050 2 0 2 14000 0 0 2 7470 12 1 1 9350 28 2 1 250 20 0 1 48479 9 3 1 3964 2 2 1 10819 5 7 1 227425 4 5 0 0 4 0 0 11600 9 4 1 0 0 0 1 28593 7 3 1 10000 5 0 0 0 5 0 0 23432 2 1 1 13800 4 3 1 101893 0 0 1 86486 8 3 1 31500 3 0 2 51525 6 1 0 3041 5 2 0 17500 0 1 2 750 1 1 2 8454 14 3 1 0 8 0 0 24896 23 0 0 14594 7 1 1 6402 0 0 1 8614 18 0 0 21585 108 0 0 6600 5 2 1 39000 3 3 1 102000 2 0 2 22500 2 1 2 15000 15 1 1 46600 4 8 1 221780 55 0 0 19492 4 4 1 0 0 0 1 37461 5 2 1 3442 7 3 1 55519 2 0 0 47259 46 1 1 36368 12 0 2 24025 0 0 2 16391 25 0 0 35100 4 6 1 16134 3 1 1 11000 3 2 1 22462 35 3 1 4958 50 3 1 11252 121 0 0 10066 55 0 0 0 0 0 0 679206 50 19 1 10000 48 0 0 5147 4 2 1 17399 3 6 1 19516 8 0 1 7374 10 4 1 29700 10 1 1 6000 9 0 1 0 0 0 1 19909 4 4 1 8566 7 1 1 71593 10 0 1 29291 8 5 1 0 0 0 1 14255 45 0 0 10000 58 0 0 0 0 0 0 71596 8 4 1 13857 4 3 1 24300 0 0 1 18000 7 1 1 26710 68 0 0 0 0 0 0 6992 3 10 1 51955 8 3 1 565 9 3 1 22806 5 6 1 43371 5 4 1 9181 5 1 0 2705 6 3 0 31678 3 3 1 46000 14 0 0 31249 3 5 1 35266 25 0 0 0 0 0 0 12726 10 8 1 5250 4 9 1 114530 7 10 1 6000 17 0 2 5000 0 1 2 31396 49 0 0 365860 43 10 0 15000 6 0 0 0 6 0 0 15150 8 1 1 0 0 0 1 31688 10 3 1 27166 3 0 1 13583 3 0 1 34580 7 0 0 12228 6 13 1 26058 10 7 1 14926 12 19 1 12500 15 0 0 58553 8 7 1 1534825 38 25 1 23500 4 0 0 214009 8 0 1 193456 17 5 1 12471 5 3 1 2414688 43 30 1 100000 59 0 0 0 0 0 0 19150 4 3 1 0 0 0 1 190203 7 4 1 25812 6 16 1 63774 2 0 1 9727 4 7 1 18325 4 0 0 9875 40 0 0 0 0 0 0 14079 0 0 0 300 8 6 1 0 0 0 1 9773 3 0 0 2000 3 0 0 522889 13 0 2 80000 4 0 2 0 0 0 2 12860 0 0 0 1903 5 0 0 20000 4 2 1 25617 8 1 1 10000 45 0 0 15000 1 0 0 10000 5 0 0 200 7 1 1 590381 42 15 1 21639 6 6 1 4100 6 2 1 0 0 0 1 713252 24 9 1 9778 4 5 0 26833 41 0 0 5677 4 2 1 2500 45 1 0 76752 5 1 1 90000 10 4 1 55246 10 7 1 22496 4 6 1 39618 3 1 1 200 4 0 1 11100 4 6 1 9635 0 0 0 10701 3 0 0 2500 3 0 0 21000 60 0 0 31500 5 0 0 66829 3 9 1 13913 0 0 0 10184 3 2 1 5000 42 1 1 1826835 47 29 1 20000 50 3 0 33179 2 0 1 650 7 2 1 5717 6 4 1 19134 28 6 1 3950 0 0 1 823 4 3 1 33856 7 3 1 16326 4 2 1 84626 12 6 1 0 0 0 1 42079 43 0 0 101560 4 5 1 33904 40 0 0 14240 12 0 0 0 0 0 0 0 25 4 1 259937 4 8 1 105766 0 14 1 26994 4 0 0 8706 0 0 0 73562 4 9 1 0 0 0 1 31000 8 3 1 18093 42 0 0 100000 6 0 2 79687 7 2 2 8556 5 3 1 8744 7 7 1 42345 25 3 1 9500 5 3 1 41149 8 2 1 11445 2 0 1 311376 8 8 1 15577 19 6 1 12280 7 3 1 332027 51 14 1 23309 22 6 1 75000 9 12 1 36928 3 6 1 25416 5 4 1 3318 8 2 1 125000 30 1 2 125000 0 0 2 17000 8 5 1 8957 8 6 1 53995 2 0 1 1596 2 1 1 102160 7 6 1 37364 40 0 0 11228 58 0 0 423 2 2 1 73817 5 3 2 2000 3 0 2 2880 7 5 1 43686 8 1 1 21502 3 0 1 18000 8 1 1 5367 4 1 0 5367 6 1 0 42807 10 3 1 0 0 0 1 9287 2 0 0 741 0 0 0 27709 10 3 1 11183 40 0 0 16367 55 0 0 428 2 2 1 21313 6 7 1 19700 148 0 0 11277 0 0 0 27462 4 6 0 100 4 1 0 20300 12 3 1 14677 8 9 1 0 0 0 1 2257 10 2 1 2444 6 2 1 0 0 0 1 206385 28 9 1 29871 9 4 1 13800 5 0 0 52900 10 8 1 0 0 0 1 250000 13 0 1 15000 12 1 1 2433 8 6 1 30000 24 0 1 233000 24 9 1 18986 15 5 1 3034 6 1 1 2066000 48 38 1 0 7 4 1 4500 7 1 1 0 0 0 1 0 0 0 1 27488 2 0 2 400 2 1 2 908916 22 22 1 7096 30 1 0 80231 10 3 0 18964 10 2 0 9159 5 3 1 38385 9 2 1 87136 6 2 1 13956 2 3 1 2074 0 0 1 10000 0 0 0 7000 18 0 0 20000 3 0 0 42525 0 0 0 11281 4 0 0 50 59 0 0 0 0 0 0 359485 23 8 1 31067 5 0 0 32350 4 0 1 19607 16 0 0 12532 4 2 0 55000 14 6 1 19765 5 5 1 11500 120 0 0 0 0 0 0 9000 9 1 1 500 5 0 1 107009 9 12 1 2249040 31 27 1 26200 5 1 1 37000 7 3 1 11300 120 0 0 9000 51 0 0 500632 23 12 1 61838 12 0 1 58727 12 0 1 11788 12 2 1 9500 12 0 1 10486 6 9 1 18500 15 0 1 200000 24 7 1 13070 28 1 1 66 0 0 1 16250 6 8 1 9000 4 2 1 0 0 0 1 20314 10 7 1 10352 0 0 2 7807 6 0 2 31818 4 1 1 4149 6 2 1 25553 4 0 0 3000 0 1 0 14347 7 3 1 200 5 1 1 0 0 0 1 0 0 0 1 0 4 4 1 35000 0 0 0 24753 1 0 0 409581 22 14 1 45800 4 6 1 24773 4 0 2 7500 4 0 2 43080 49 0 0 14074 0 0 0 16000 10 1 1 14938 3 0 0 133889 8 15 1 10048 5 3 1 24380 8 10 1 10000 30 0 0 7203 8 3 1 710473 28 27 0 52109 3 1 0 25387 6 1 0 11450 5 2 1 264305 20 5 1 23371 59 0 0 3766 10 1 1 38890 40 0 0 30134 8 2 1 1728 5 6 1 82172 34 3 1 27000 3 0 2 8385 3 0 2 25877 24 1 1 0 0 0 1 43000 9 0 1 13756 0 0 2 12744 7 1 2 5184 6 7 1 11100 5 0 0 81000 4 2 1 9725 4 3 1 52424 21 3 1 29188 5 3 1 14577 0 1 1 265 0 0 1 0 0 0 1 0 10 14 1 15020 6 7 1 8400 60 0 0 0 0 0 0 125089 5 4 1 4400 3 11 0 20000 47 0 0 16587 7 5 1 7105 4 0 2 5000 1 1 2 50000 60 0 0 33458 19 3 1 19355 4 4 1 9666 8 0 2 5000 7 0 2 50503 0 0 0 10004 4 6 0 2332 0 1 0 19573 5 6 1 14323 9 2 1 30000 1 0 0 10547 9 2 1 11500 2 0 1 14140 45 2 1 13191 9 4 1 20092 5 11 1 77000 7 6 1 0 0 0 1 28036 41 0 0 46288 10 5 1 766 5 4 1 10000 0 1 0 9996 8 0 0 108152 7 1 2 76434 8 0 2 476937 20 11 1 15000 2 1 2 15000 8 0 0 10900 5 4 1 60000 22 13 1 14000 65 0 0 57909 10 5 1 10250 8 0 0 8286 0 0 0 46570 5 3 2 0 7 0 2 14815 5 5 1 17189 4 1 1 15378 9 0 1 35000 24 0 0 19897 0 0 0 2500 4 0 0 21011 4 4 1 300 0 0 1 18667 4 1 0 110316 2 0 0 0 2 0 0 16366 10 0 0 6509 0 0 0 11152 3 0 1 3926 6 1 1 74732 6 0 1 37110 15 7 1 75000 8 3 1 14370 6 4 1 9936 5 1 1 22233 5 0 1 12176 7 4 1 2006870 44 39 1 25000 10 0 2 15000 15 0 2 48400 8 4 2 17224 8 0 2 7072 3 2 1 4866 35 0 0 23809 3 1 2 0 0 0 2 155000 32 6 1 23000 0 4 1 0 25 0 1 5182 5 4 1 17858 4 0 0 22548 3 2 1 0 10 11 1 2106 8 3 1 8559 6 2 1 6528 6 2 1 0 0 0 1 100 3 3 0 77099 4 5 1 500 3 0 1 3900 5 11 1 0 0 0 1 10958 7 5 1 22753 15 0 0 74745 75 0 0 0 0 0 0 11454 56 0 0 19374 30 0 0 10478 7 3 1 31971 43 0 0 40000 4 1 0 16500 25 1 1 26139 1 6 1 6713 4 5 1 22475 35 21 1 27786 39 0 0 60000 18 1 2 10000 0 0 2 10163 12 1 1 0 0 0 1 25808 7 0 0 846 4 0 0 27 0 0 0 1108826 46 33 1 48935 3 4 1 1000 5 0 0 10000 80 0 0 0 0 0 0 56000 8 3 1 52500 31 11 0 21010 5 0 0 0 0 0 0 14975 32 1 1 21428 7 0 0 16102 8 1 0 9518 6 5 1 36000 1 0 0 18000 6 0 1 6000 2 2 1 1900 47 1 1 52985 0 0 0 0 20 0 0 114058 3 5 1 30000 4 3 1 40416 7 0 2 679 3 1 2 12014 3 0 0 265 0 0 0 2300 7 2 2 200 3 3 2 8424 4 3 1 200 35 0 0 8000 24 1 1 16312 34 0 0 25000 30 0 0 64857 5 4 1 9400 0 1 1 453741 23 14 1 22021 4 0 1 7000 6 1 0 4464 49 0 0 685272 0 2 0 152061 9 1 0 16349 6 5 1 10000 8 3 1 3500 5 4 1 4600 9 2 1 700 1 0 0 45226 5 4 1 26700 9 7 1 25200 7 4 1 190000 3 0 2 165000 0 0 2 86457 2 3 1 16004 8 1 1 42000 3 0 1 25000 108 0 0 26591 7 4 1 72405 10 6 1 17000 2 1 0 900 8 0 0 15000 30 0 0 58426 9 12 1 35808 20 0 0 45000 23 8 1 12621 9 8 1 16500 3 0 0 500 40 0 0 30000 9 0 2 0 0 0 2 169800 8 4 2 10000 1 0 2 12500 60 0 0 35000 2 0 0 22000 1 0 0 15000 4 0 0 225568 24 5 1 9347 4 6 1 235500 13 13 1 617 5 5 1 22400 100 0 0 9553 5 18 1 0 2 7 1 2888 46 1 1 8000 5 3 1 8200 37 1 1 20000 5 0 2 0 3 0 2 200000 33 0 0 22000 25 0 0 876300 30 4 0 5018 7 2 1 25000 4 4 1 63380 3 0 2 33 7 0 2 35000 35 0 0 0 0 0 0 54229 2 0 2 18400 3 1 0 400000 25 9 1 9221 9 2 1 0 0 0 1 56408 15 3 1 500 22 0 0 100 17 0 0 0 0 0 0 20000 5 1 1 3200000 59 3 0 0 0 0 0 20000 38 0 0 24369 7 1 1 173276 13 2 0 9500 8 0 1 25000 7 5 1 18100 10 1 0 0 0 0 0 10000 3 0 0 0 0 0 0 17322 4 2 1 28000 5 1 2 8224 20 1 2 52180 7 3 1 295607 0 7 2 75000 6 0 2 161793 7 0 0 1600 1 1 0 20200 40 0 0 300000 69 0 2 8058 0 0 2 51483 9 6 1 13200 6 2 1 38763 7 5 1 50635 5 0 1 31262 8 5 1 42050 20 12 1 1339302 54 0 0 21725 6 2 1 1300 3 2 1 24284 8 3 1 16920 5 1 1 0 0 0 1 101769 11 3 1 96000 7 6 1 16897 4 1 1 17000 125 0 0 45855 3 0 0 10936 16 0 0 10149 10 0 0 13861 25 0 0 14000 7 0 1 42038 8 6 1 30676 4 1 1 24500 8 4 1 45785 6 7 1 1588 7 1 0 257 2 0 0 61829 2 0 0 4063 7 1 0 200230 10 6 2 21206 5 1 2 20000 1 0 0 14900 28 0 0 1000 35 1 1 3000 3 5 1 182755 10 1 1 840586 48 21 1 706972 15 28 1 7700 6 5 1 30848 6 3 1 3545 9 3 1 49000 9 3 1 113000 9 5 1 15000 2 5 1 88636 4 0 0 0 0 0 0 11200 60 0 0 0 0 0 0 18000 2 0 0 986 6 0 0 9600 1 2 1 82750 7 6 1 0 1 0 1 106000 25 10 1 36338 4 5 1 296 0 1 1 57000 8 5 1 13927 0 1 0 9100 0 1 0 30328 4 3 1 12032 4 2 1 13500 5 0 1 9500 55 0 0 0 0 0 0 18349 2 3 1 69883 10 2 1 55000 60 0 0 0 0 0 0 3500 10 3 1 0 0 0 1 16000 0 0 0 16200 8 4 1 3100 0 0 1 40000 6 2 1 9240 5 0 0 61352 9 4 1 11410 49 0 0 38500 10 8 1 13015 5 7 1 5450 3 5 1 15928 8 0 0 20350 3 1 1 9300 3 2 1 0 0 0 1 76882 48 5 1 0 0 0 1 591 8 4 1 53811 7 3 2 7094 7 2 2 4329 0 0 2 2825 3 0 2 21017 4 10 1 25362 5 5 1 0 0 0 1 946052 45 17 1 40000 5 2 1 105205 60 3 0 38861 3 11 1 18582 3 0 2 1000 0 0 2 180000 6 7 1 27650 5 0 1 89472 13 18 1 56378 15 4 1 16059 7 4 1 888 0 0 1 0 0 0 0 9900 5 0 1 30000 22 0 0 24152 18 7 1 6377 3 1 1 48693 8 5 1 500 0 0 1 159789 7 5 1 8000 3 11 1 28000 5 2 1 10000 9 9 1 10000 5 0 1 11300 5 0 1 9502 8 1 1 0 0 0 1 50546 0 15 1 130000 10 3 1 250648 16 15 1 344195 20 8 1 9000 29 1 1 0 0 0 1 1982 9 3 1 34249 6 3 1 47766 36 14 1 23500 4 4 0 4500 0 2 0 6000 0 0 2 6000 5 0 2 3500 5 1 1 6000 5 0 1 6000 5 1 1 0 0 0 1 12753 5 0 0 84434 23 5 1 300 5 1 1 18660 2 5 1 1014 8 4 1 9804 4 1 2 2776 7 0 2 22500 5 0 1 114910 10 4 1 62783 5 3 1 36490 7 8 1 0 0 0 1 0 0 0 1 7301 0 0 0 6340 5 0 0 50000 50 0 0 590491 25 8 1 1033000 47 24 1 215000 25 0 0 3018 0 0 2 1474 52 0 2 12705 4 15 1 8000 7 5 1 45500 9 4 1 34253 12 5 2 0 0 0 2 1112 40 1 1 20059 1 0 2 20059 0 0 2 25200 0 8 1 1125 5 5 1 13000 5 3 1 180 5 0 1 21921 3 0 1 0 0 0 1 25532 7 7 1 9852 0 1 1 30000 1 0 0 75200 9 5 1 0 0 0 1 31138 7 10 1 13214 24 0 0 2228845 36 28 1 64359 8 3 1 5071 5 4 1 15000 69 0 0 0 0 0 0 9877 70 0 2 500 0 0 2 13600 4 2 0 50 47 0 0 203963 13 1 1 11348 0 3 1 7493 9 6 1 18500 0 0 2 0 11 0 2 600 19 0 1 10853 7 8 1 16973 6 6 1 15731 0 0 0 0 2 0 0 1457 3 3 1 9840 5 1 1 3595 5 1 1 0 0 0 1 327829 37 10 1 1641447 60 41 1 1200 2 3 1 17000 0 1 2 962 39 0 0 1000 7 0 1 23043 10 2 1 80000 0 0 0 920 2 0 0 5400 5 1 1 1100 0 1 0 7506 5 3 1 34600 13 7 1 2100 4 4 1 3795 5 1 1 983 35 0 0 60100 2 4 2 24320 0 7 2 39067 4 10 1 57842 10 4 1 16382 4 1 1 95000 0 2 1 263 0 2 1 5429 45 0 0 214254 45 0 0 5000 7 6 1 11300 10 0 1 36585 9 4 1 573991 25 11 1 10179 9 0 0 491 8 0 0 80000 17 1 1 0 0 0 1 76628 14 1 2 25000 1 0 2 219013 24 11 1 50449 6 0 1 13991 14 0 1 0 0 0 1 15251 5 0 0 12843 2 0 0 21000 3 0 0 14670 10 1 0 1509 0 1 0 24500 20 1 1 9430 8 2 1 716769 23 12 1 14042 10 1 1 8421 10 2 1 14000 6 1 0 5200 0 2 0 50100 50 0 0 34500 52 0 0 80000 23 0 1 10000 4 1 1 9144 4 2 1 96503 25 7 1 200000 10 8 1 11064 5 1 1 126737 4 7 1 300 1 0 1 94250 8 6 1 2635 0 0 1 84455 70 0 0 0 0 0 0 953479 16 16 1 37032 5 7 1 4997 17 0 0 872562 22 18 1 1000000 62 0 0 4500 25 1 1 10800 3 15 1 1600 4 3 1 14335 37 0 0 12000 5 0 1 30385 1 0 1 5330 3 6 1 44403 10 3 1 12003 6 0 0 12000 5 1 1 0 0 0 0 10000 5 6 1 595 5 2 1 24922 5 2 1 38000 42 0 0 13250 3 3 1 21800 10 0 0 28800 6 6 1 1092 25 1 1 0 0 0 1 20386 5 2 0 10127 0 2 0 0 0 0 0 36262 5 0 1 12000 29 0 0 97921 4 3 0 10500 0 0 0 15014 4 10 1 49000 10 2 1 8200 47 0 0 19631 5 4 1 5123 7 7 1 81911 6 4 1 600 7 2 1 26831 11 1 0 33966 10 5 1 29413 79 0 0 0 0 0 0 9400 6 0 2 9000 0 0 2 21922 12 0 0 8500 7 2 1 200 7 1 1 95000 8 5 1 3500 6 1 1 676333 25 17 1 394759 8 1 0 61120 3 0 0 0 0 0 0 0 2 0 0 48000 4 0 1 5653 7 1 1 37000 70 0 0 0 0 0 0 25000 78 0 0 0 0 0 0 65315 8 3 1 31754 1 0 1 30000 5 6 1 7000 10 6 1 23750 7 4 1 0 35 0 0 21689 5 2 1 34900 10 7 1 16200 5 5 1 28846 10 3 1 23532 3 5 1 2020904 0 0 1 287799 42 12 1 17797 5 7 1 0 0 0 1 11700 5 0 0 10000 40 0 2 0 0 0 2 8300 9 4 1 42817 7 4 1 100000 10 6 1 14395 6 1 2 2203 0 0 2 26200 7 7 1 22282 0 0 1 9456 8 2 1 825 3 0 1 0 10 0 1 23662 0 1 2 1448 10 0 2 13154 7 1 1 31064 2 4 1 3500 2 1 1 3850 6 2 1 25000 0 0 0 202000 0 5 1 33463 8 6 1 640 4 3 1 25000 50 0 0 4662 32 2 1 17500 13 0 0 15335 7 5 1 10000 15 0 0 6348 4 9 1 21236 6 0 0 3000 0 0 0 52997 4 4 1 0 0 0 1 15331 8 3 1 237767 18 11 1 40000 10 2 1 18000 10 2 1 14360 2 1 2 4500 2 0 2 888227 33 22 1 21000 60 0 0 0 0 0 0 83412 79 0 0 0 0 0 0 3500 5 1 1 9831 45 0 0 261337 17 6 1 9000 2 1 1 0 0 0 1 1934 4 5 1 0 0 0 1 10000 5 0 0 9270 3 0 1 29696 4 8 1 0 0 0 1 9251 8 1 1 10000 3 2 1 87217 7 7 1 10500 6 3 1 1727600 39 31 1 13877 7 7 1 2500 49 0 0 17331 7 7 1 19928 60 0 0 13420 40 0 0 15170 3 4 1 12000 4 2 0 2009399 46 44 1 2703 7 0 1 5042 9 6 1 15200 25 0 0 36092 10 4 1 14460 0 0 0 0 0 0 0 50210 0 0 0 18000 56 0 0 200072 10 1 1 42897 5 5 1 16000 42 0 0 338 5 5 1 95000 6 6 1 22308 0 1 1 24900 90 0 0 80000 8 3 1 62636 0 0 1 40265 38 0 0 9810 0 0 0 10000 3 0 0 15905 5 5 1 193083 7 4 1 0 0 0 1 18350 8 8 1 25000 6 0 2 3000 0 0 2 48000 5 0 1 1800 7 2 1 0 0 0 1 22944 50 0 0 421198 21 11 1 12000 25 2 1 8000 1 3 1 45812 30 0 127466 5 2 2 73516 0 0 2 26400 17 11 1 3212 5 3 1 16169 25 1 0 70182 2 5 2 6375 4 1 2 144097 5 4 1 29048 5 7 1 26000 110 0 0 1250 4 1 1 23000 9 5 1 120530 17 7 1 89500 19 11 1 1602 6 4 1 16161 29 2 1 10000 61 0 0 60923 2 4 1 12718 55 0 0 74860 10 7 1 20000 10 0 0 51584 4 4 1 336 3 3 1 20942 0 0 0 18200 3 1 0 4620 4 0 1 5700 4 2 1 128651 10 5 1 75201 20 0 0 20000 5 0 0 50000 5 8 1 7869 8 5 1 32639 3 1 1 13646 20 0 0 55548 10 9 1 23967 4 7 1 13685 50 0 0 3030 9 2 1 27222 80 0 0 1047156 42 16 1 16477 1 0 2 1000 3 0 2 24438 2 8 1 6231 5 3 1 13200 3 1 1 0 0 0 1 6000 40 1 1 49770 5 16 1 120000 18 1 1 5332 8 3 1 13500 9 6 1 150 9 5 1 4425 3 1 1 3392 0 1 1 250805 0 17 0 213863 0 26 0 38575 0 0 0 25250 0 0 0 13550 7 4 1 34275 6 7 1 0 0 0 1 0 0 0 1 41000 10 5 1 19446 0 0 2 47 5 0 2 10000 1 0 0 27571 1 1 1 623888 23 14 1 37624 8 0 2 11000 8 0 2 18765 3 0 0 19322 2 2 2 16200 4 0 0 106728 2 5 1 7850 6 2 1 625 0 1 1 13767 8 4 1 1371103 49 19 1 10000 6 2 1 90421 4 3 1 0 39 0 0 21994 6 6 1 102769 50 12 1 24477 12 2 1 50000 12 0 0 36000 2 1 2 19000 3 0 2 39500 8 3 1 18000 57 0 0 404000 31 0 0 49851 0 1 0 1237 8 6 1 0 0 0 1 39563 7 10 1 46250 10 0 1 23519 12 0 0 13500 5 1 1 402 4 2 1 28274 9 6 1 16954 4 2 1 20150 1 0 0 266984 9 11 1 938419 33 18 1 10000 76 0 0 0 0 0 0 10500 4 1 1 251683 10 22 1 0 0 0 1 15000 4 0 1 6900 23 1 1 11705 2 0 0 0 4 0 0 20738 9 12 1 1883021 46 43 1 19885 13 2 1 15226 28 0 0 18286 5 4 1 20000 0 0 0 0 5 0 0 16063 5 0 1 300 5 1 1 10000 20 1 1 13148 9 7 1 50000 5 5 1 9400 10 7 1 9600 2 4 1 40000 3 1 1 13438 9 10 1 63182 3 11 1 1329954 39 31 1 60125 6 4 1 4875 0 1 1 20857 0 0 0 2423 4 0 0 7300 1 1 1 300000 2 16 1 327800 21 12 1 6300 9 3 1 500 15 0 1 200 4 1 1 5000 10 0 0 25669 10 1 1 100 2 0 1 30036 2 0 1 25000 10 3 1 2900 4 5 1 129275 10 4 1 18500 6 1 1 25000 35 0 0 295812 41 5 1 128000 15 0 0 6000 0 0 0 11089 18 0 0 91804 19 8 1 41366 20 13 1 58040 3 2 1 154463 5 6 1 19376 7 5 1 1202 46 0 0 50000 0 0 2 30000 5 0 2 41290 10 4 1 5280 3 0 1 136726 77 1 0 0 0 0 0 71958 7 2 1 15046 2 8 1 63469 10 3 1 0 0 0 1 6300 6 3 1 0 0 0 1 23000 10 1 1 0 0 0 1 70668 6 0 0 3733 7 2 0 81358 3 2 1 54470 9 8 1 46396 10 1 1 159639 8 6 1 750 7 3 1 9800 4 4 1 8850 0 2 1 9146 44 0 0 38000 37 0 0 114514 10 6 1 86796 5 4 1 132000 4 0 2 0 0 0 2 1259300 43 29 1 75000 78 0 0 44596 0 1 0 32804 0 1 0 8219 12 1 0 500 28 0 0 12500 6 0 1 0 0 0 1 206110 3 4 1 68897 5 0 2 0 7 0 2 25000 2 0 2 20661 2 4 1 1600 5 8 1 180000 5 4 1 300592 21 16 1 336 4 3 1 16869 0 0 0 11395 12 1 0 90000 0 2 2 20500 10 0 0 500 5 0 0 40000 8 0 0 0 0 0 0 11101 2 6 1 84896 8 2 1 35000 5 0 1 23329 3 3 1 1782 7 2 1 60000 0 0 0 10000 2 1 0 127600 0 0 0 27000 5 6 1 40615 0 0 2 30000 24 0 2 50000 44 0 0 256 4 1 1 53576 7 2 1 18249 42 0 0 35000 75 0 0 0 0 0 0 13500 10 7 1 11130 5 1 1 60600 7 2 1 74284 10 2 1 13998 14 1 1 0 0 0 1 12250 2 2 1 457149 10 0 0 47919 0 0 0 16762 7 7 1 104600 10 12 1 5200 47 1 1 200 2 0 1 35668 8 3 1 9882 6 2 1 61772 7 8 1 1052808 46 9 1 19396 9 7 1 114111 10 27 1 30000 75 0 0 0 0 0 0 10930 10 4 1 22079 3 0 1 20000 14 1 1 67190 8 1 1 10798 5 1 1 16218 3 0 2 14557 3 0 2 22088 45 0 0 50000 7 6 1 225000 10 5 1 224 6 2 1 5573 3 3 0 4000 0 0 0 10000 8 0 1 19500 75 0 0 0 0 0 0 8700 8 7 1 223914 7 5 1 30000 0 0 1 8500 43 0 0 10133 0 4 2 500 14 0 2 7465 4 0 1 27116 4 3 1 91772 5 5 1 11000 0 0 0 100 3 0 0 22000 6 3 1 20000 4 0 0 1100 4 2 0 64928 30 9 1 42150 4 6 1 15542 4 1 1 13500 7 9 1 69030 7 7 1 9260 5 5 1 6728 4 8 1 0 0 0 1 174330 3 0 2 63119 2 1 2 14600 8 1 1 2505 3 5 1 40000 20 0 0 26073 5 5 1 12700 8 0 1 2900 8 0 1 25754 7 3 1 40021 0 1 0 150 4 1 0 200 5 0 0 100000 45 0 0 12861 59 0 0 18000 24 3 1 10467 0 0 0 40156 5 9 1 21405 63 0 0 0 0 0 0 19024 0 2 0 7953 2 0 0 7747 0 0 0 232617 9 4 1 407464 0 0 0 9400 6 4 1 34500 150 0 0 200485 10 6 1 20000 2 0 0 50000 5 3 1 13260 10 0 0 52400 8 4 1 0 0 0 1 6056 48 1 1 2498 50 0 0 30705 10 3 1 190 0 1 1 125670 10 1 0 0 0 0 0 51062 8 9 1 22200 0 4 1 18400 9 4 1 6611 6 3 2 3067 0 3 2 14866 5 1 1 10000 4 1 1 12750 5 0 2 297986 8 7 1 0 0 0 1 0 0 0 1 29000 8 3 1 16664 6 2 1 9830 2 4 1 148245 2 3 1 18000 0 2 1 17563 35 0 0 29213 0 0 2 2919 4 1 2 20062 6 6 1 300 4 3 1 11000 10 1 1 5708 5 5 1 16300 6 0 0 11000 0 0 0 9000 7 0 0 0 3 0 0 361200 5 10 1 59000 12 0 0 45740 5 11 1 0 0 0 1 253875 10 7 1 33243 39 0 0 1544 1 6 1 11394 9 4 1 29200 1 4 1 39215 0 0 1 26338 4 2 1 293 30 1 1 10000 9 0 1 12000 30 2 1 7507 4 2 1 61288 4 4 1 48000 50 0 0 21686 5 2 1 134897 1 10 1 12000 6 0 1 7500 4 1 1 58960 4 6 1 32000 4 1 1 8224 2 3 1 14677 4 0 0 2472 12 1 0 2595780 25 20 1 8849 24 3 1 10602 4 3 1 11926 8 8 1 3153 13 1 1 16225 10 2 1 0 0 0 1 2617 3 1 1 9816 0 0 0 9816 5 0 0 4880 30 1 1 80000 2 16 1 10543 4 0 0 25758 7 3 1 819118 28 19 1 0 0 0 1 13000 25 3 1 45000 0 16 1 60000 13 1 1 13510 5 1 1 50000 10 8 1 45602 4 14 1 2485296 49 40 1 383552 48 23 1 9458 25 0 0 0 0 0 0 17241 50 0 0 0 0 0 0 10000 7 2 1 25848 12 3 1 2412174 26 7 2 26061 8 5 2 24047 66 0 0 0 0 0 0 7763 4 2 0 11000 3 0 0 30000 7 0 0 19946 78 0 0 47103 6 4 1 15000 9 0 1 0 0 0 1 10650 7 11 1 104533 5 3 1 11500 4 3 1 7052 8 1 1 1880 3 1 1 10270 10 1 1 4500 9 7 1 1342565 54 9 1 61846 9 4 1 57766 7 8 1 15892 5 4 1 75045 6 1 1 0 0 0 1 9000 8 2 1 9809 10 0 2 6700 10 0 2 2200 5 1 0 600 8 1 0 17506 8 3 1 156000 25 6 1 12000 0 1 2 3000 5 0 2 21800 10 2 1 7948 7 0 0 2424 7 0 0 8096 7 2 1 10000 8 1 1 44500 8 6 1 12888 2 3 1 100491 15 0 0 23198 9 3 1 5000 7 3 1 10075 2 0 0 7900 4 1 1 13058 4 5 1 0 0 0 1 9450 4 4 1 3295 5 1 1 135638 47 5 1 67068 8 14 1 42118 4 3 2 1050 0 0 2 11794 0 1 2 2000 4 0 2 9237 2 0 0 416 0 0 0 14025 2 0 1 9000 8 0 1 1290 3 3 1 0 3 0 1 37279 6 8 1 100000 38 0 0 39000 8 5 1 662076 25 13 1 35081 7 2 1 22253 2 0 0 8017 0 0 0 30000 2 0 0 23152 5 5 1 27205 7 0 0 612 0 0 0 12859 18 0 0 15815 5 0 0 300 2 2 1 123913 10 3 1 30000 48 0 0 40578 7 0 2 12000 4 0 2 42870 3 2 2 13500 5 2 2 22068 6 2 1 124293 1 4 2 42308 4 2 2 7000 4 4 1 0 0 0 1 0 0 0 1 10700 2 4 1 500000 6 1 1 17101 7 4 1 9077 6 0 2 3200 0 0 2 31000 5 0 1 13420 45 0 0 40291 77 0 0 0 0 0 0 336 6 3 1 20744 50 0 0 30000 3 0 1 13200 10 4 1 7233 5 2 1 42793 6 3 1 13650 0 0 2 10544 4 2 1 5376 5 3 2 1902 5 0 2 71300 38 2 1 40000 5 1 2 21369 3 0 2 0 5 8 1 224 7 2 1 105000 5 0 1 100 29 0 0 1575 10 1 1 178591 1 9 1 15000 4 4 1 4664 8 2 1 11000 15 2 1 230874 11 0 1 55399 4 0 1 8000 13 4 1 400 0 0 1 15000 20 0 0 1400 10 1 1 13420 35 0 0 11499 66 0 0 12267 5 2 1 2793 6 6 1 545 0 0 1 1181910 14 9 2 454735 29 5 2 10065 2 1 0 0 4 0 0 5600 5 5 1 111335 27 0 0 14601 11 2 1 0 0 0 1 59388 10 5 1 16092 7 7 1 38569 10 5 1 52198 7 4 1 20372 9 0 1 4500 5 1 1 382 0 1 0 49 5 0 0 15663 55 0 0 24654 4 2 1 70000 5 5 1 12352 6 5 1 10000 9 11 1 464370 52 25 0 13681 3 1 1 88907 8 4 1 28100 9 2 1 86872 0 1 1 17644 6 3 1 18096 19 2 1 190000 10 8 1 10500 17 0 0 42548 16 3 1 79338 13 8 1 36000 40 0 0 20000 8 0 0 0 0 0 0 13526 4 0 0 0 0 0 0 0 8 0 0 14000 3 0 0 11468 5 3 1 18415 37 0 0 35000 56 0 0 14500 21 2 1 62000 0 13 1 8250 0 0 0 4500 1 0 0 40447 8 5 1 15000 42 0 0 28200 7 6 1 43109 5 0 0 126845 0 3 0 59024 6 2 0 61463 8 1 1 7000 1 1 1 118000 1 0 1 20000 4 0 1 20255 23 0 0 4500 71 0 0 0 0 0 0 84280 6 0 1 52184 40 5 1 1402005 28 23 1 12950 5 0 2 12900 5 3 2 30000 6 5 1 5000 0 0 1 0 0 0 1 0 1 0 0 0 4 0 0 520905 9 12 1 16549 8 1 1 59801 4 3 1 11186 0 2 1 15000 79 0 0 0 0 0 0 2568 22 1 1 0 5 0 0 337 4 2 1 180920 6 9 1 15000 16 0 1 8478 5 17 1 0 0 0 1 10000 125 0 0 9200 7 4 1 7997 48 2 1 0 0 0 1 26613 3 5 1 5000 14 0 2 4022 0 2 2 10342 8 3 1 13203 3 0 0 10137 4 1 0 2848 4 2 1 14873 5 2 1 115000 2 6 0 17000 110 0 0 14000 40 0 0 0 0 0 0 12000 5 0 0 1000 1 0 0 9680 1 14 1 7750 28 1 1 14458 45 0 0 6550 4 2 1 881978 31 19 1 6200 10 1 1 15725 6 4 1 113 2 0 0 30288 5 2 1 2676 9 2 1 0 0 0 1 70000 46 2 1 17488 3 3 2 1100 0 2 2 12000 0 0 0 3018 4 0 0 116400 2 0 0 10622 4 2 1 70127 0 0 1 13185 57 2 1 8800 4 3 1 10000 4 2 1 16000 35 0 0 20983 60 0 0 0 0 0 0 33000 2 1 0 76000 5 6 1 0 0 0 1 22817 40 0 0 18464 3 0 1 15722 3 1 1 10408 7 2 1 11750 8 5 1 17000 60 0 0 2600 25 1 1 40000 0 0 0 500 0 0 0 31000 4 3 1 8500 30 0 0 0 0 0 0 7683 5 4 1 465923 18 4 0 50000 6 14 1 0 0 0 1 12000 12 2 0 48514 5 8 1 24112 4 4 1 12000 7 0 0 351231 19 8 1 9502 67 0 0 11750 69 0 0 0 0 0 0 12000 2 1 0 4500 2 0 0 26877 3 4 1 14095 50 0 0 10859 9 6 1 13635 0 0 0 2655 4 0 0 36000 58 0 0 19953 0 0 0 14800 2 0 0 50918 18 10 1 30602 9 9 1 30350 5 0 1 110 2 1 1 2283887 53 40 1 8561 5 5 1 2054 0 0 1 63537 5 5 1 2555 4 3 1 0 0 0 1 65000 4 1 2 0 0 0 2 82892 11 7 1 90389 0 11 1 5628 49 1 1 5030 13 2 1 0 0 0 1 59000 10 3 1 16800 6 4 1 0 0 0 1 202000 32 13 1 0 0 0 1 20000 10 0 0 4000 2 0 0 16958 13 0 0 17304 1 0 0 8765 9 6 1 5300 45 0 0 18950 3 2 1 175496 6 4 0 4618 6 1 0 20000 5 0 0 36000 2 4 1 8505 5 1 1 26460 9 1 1 0 0 0 1 14000 4 1 0 20112 10 0 0 14714 5 0 0 5000 10 0 0 20000 3 4 1 17800 1 4 1 10050 0 3 1 9827 6 1 0 3953 0 1 0 95149 5 4 1 44211 3 2 1 12900 6 3 1 44805 5 0 1 0 0 0 1 71136 7 0 2 43217 3 1 2 23100 10 9 1 17500 40 0 0 8395 5 3 1 45970 25 5 1 60100 8 0 1 9200 7 0 1 12500 8 1 1 60000 8 1 1 18150 7 2 0 11000 4 2 0 49770 5 16 1 20000 7 2 1 74658 9 3 1 8617 0 0 1 145420 47 16 1 4357 5 5 1 60000 20 1 0 43540 3 5 1 1617133 34 24 1 1500 5 1 1 17522 4 0 0 10424 0 0 0 1000 48 0 0 10000 0 1 1 5000 5 0 1 19900 5 2 1 17000 17 4 1 4858 4 2 1 2927 0 0 1 21341 4 6 1 3000 5 1 1 10690 3 0 2 10690 0 0 2 1000 5 3 1 85546 7 2 1 23695 36 0 0 75000 6 0 0 35000 0 0 0 0 3 0 0 7483 5 1 0 2273 5 1 0 10200 9 1 1 77382 5 2 1 0 0 0 1 10000 53 0 0 72946 4 4 1 365332 12 4 2 11000 5 0 2 371977 33 18 1 5168 10 3 1 17929 75 0 0 16390 75 0 0 17929 75 0 0 100000 0 6 1 4000 4 4 1 61969 4 0 2 15578 1 0 2 20694 5 0 0 835 3 0 0 13858 3 6 1 50 0 0 1 18217 4 0 1 250 4 1 1 44138 4 1 0 0 0 0 0 643434 4 14 1 26650 44 7 1 0 2 0 0 3000 48 0 0 350000 28 0 2 254069 14 7 2 18000 0 0 0 0 2 0 0 119112 10 4 1 82000 0 1 1 2000 37 0 0 4500 5 1 1 25134 2 1 1 60000 1 0 0 10847 2 0 0 45000 7 5 1 21900 0 0 0 0 0 0 0 35000 7 6 1 0 0 0 1 10000 5 0 0 0 0 0 0 27433 6 3 1 0 0 0 1 0 30 0 0 14500 5 4 1 30305 10 0 2 27082 0 2 2 14632 5 0 0 0 5 0 0 16681 7 0 0 224 0 0 0 7600 3 2 1 2100 0 0 1 11600 30 0 0 0 0 0 0 3730 3 4 1 8201 7 10 1 40000 0 0 0 0 10 0 0 27200 5 10 1 6000 4 2 1 0 0 0 1 10050 4 0 1 11200 5 3 1 0 0 0 1 25000 0 0 2 5000 16 0 2 6000 0 0 1 5500 6 5 1 9450 7 5 1 5800 4 5 1 0 0 0 1 11120 3 0 1 16370 4 0 2 3260 0 0 2 21350 3 4 1 0 0 0 1 500 3 1 1 110000 6 4 1 61756 22 10 1 65895 8 2 1 72705 5 18 1 11862 3 3 1 12211 0 0 0 17200 6 3 1 95612 4 8 1 10000 4 0 0 1150 7 6 1 15000 7 0 2 10000 5 0 2 433698 41 26 1 1127 4 4 1 100 0 0 1 40350 8 0 1 38581 3 1 1 20000 3 1 1 30000 10 0 0 994 10 4 1 11600 5 3 1 1554 1 4 1 15000 4 1 1 78226 50 0 0 0 0 0 0 36348 11 0 0 2000 43 0 0 700 20 1 1 12895 3 0 1 103700 3 6 1 58231 4 16 1 35500 2 0 0 0 5 0 0 225000 23 9 1 11271 6 5 1 7456 5 0 1 5000 43 0 0 2500 5 1 1 11300 7 6 1 2050800 48 38 1 12882 4 0 2 0 3 1 2 50000 75 0 0 2000 40 0 0 65000 10 1 1 41620 8 10 1 500000 34 8 1 2275 0 1 1 68598 7 11 1 346079 23 12 1 33532 9 6 1 107585 5 4 1 0 0 0 1 10000 0 0 0 266050 14 11 1 28000 9 0 0 15500 7 0 0 4591 5 5 1 777 3 3 1 102265 52 19 0 23301 9 0 0 7220 0 0 0 110000 43 5 1 5000 7 1 2 0 0 0 2 0 6 0 0 1835742 41 50 1 26400 9 6 1 0 1 0 1 17000 135 0 0 24500 10 1 0 24500 0 1 0 10000 45 0 0 67150 25 6 1 52884 5 14 1 5700 4 4 1 2508 4 1 1 25000 10 7 1 0 0 0 1 15568 5 5 1 8669 0 0 1 313 5 1 1 30560 20 0 0 0 0 0 0 40352 60 0 0 0 0 0 0 10000 30 0 0 0 0 0 0 30000 50 0 0 0 0 0 0 12157 42 1 1 500000 42 1 1 12000 22 0 2 5000 12 0 2 4800 0 0 0 32399 9 11 1 41145 7 8 1 301540 20 4 1 12000 3 5 1 41300 9 4 1 700 0 0 1 11900 4 6 1 216 5 1 1 6057 10 4 1 15000 79 0 0 500 30 0 0 10000 60 0 0 0 0 0 0 10200 19 0 0 0 0 0 0 10171 40 1 1 257 8 1 1 15000 0 1 0 5000 7 0 0 0 7 0 0 96303 15 0 0 17583 2 7 1 25000 10 0 0 0 0 0 0 800 50 0 0 28335 1 1 0 739 1 1 0 84143 50 2 0 35958 2 0 1 15759 0 0 2 2544 40 0 2 171192 4 5 0 43556 8 1 0 48336 15 3 1 13918 0 0 0 0 0 0 0 1659 10 2 0 19000 75 0 0 47360 6 0 2 225 5 1 1 26864 2 1 2 16476 2 2 2 17750 7 1 0 42000 9 4 1 0 0 0 1 9850 4 8 1 15000 3 0 1 171000 21 3 1 0 0 0 1 18000 35 0 0 19000 25 0 0 0 0 0 0 41626 60 0 0 2000 52 0 0 15000 5 0 2 1824 5 2 2 60028 4 0 2 10000 0 0 2 6255 125 0 0 14000 20 0 0 0 0 0 0 11000 4 19 1 0 0 0 1 13989 5 3 1 35111 45 0 0 9300 5 2 1 20647 3 1 0 225 0 2 0 219988 18 9 1 29072 40 0 0 38000 32 0 0 42997 7 3 1 15000 0 0 1 11735 66 0 0 12650 8 2 2 3000 0 0 2 5546 24 1 1 3300 8 1 1 0 26 0 0 895947 27 21 1 9540 28 0 0 120400 11 5 1 50 5 0 0 15767 9 0 1 68435 9 8 1 95000 5 2 1 13560 20 0 0 0 0 0 0 20331 7 12 1 339 6 3 1 12500 4 0 1 84035 10 5 1 32000 8 5 1 31038 8 5 1 167 0 1 1 119000 26 9 1 23316 4 6 1 0 4 6 1 506000 0 0 0 0 0 0 0 6200 7 4 1 524656 40 17 1 11546 5 0 2 1681 0 0 2 9000 5 2 1 16355 41 1 1 5000 54 0 0 0 0 0 0 52947 3 4 1 17000 3 3 1 15357 48 0 0 0 0 0 0 25000 34 0 0 16714 10 7 1 82995 3 2 1 4000 0 0 1 361100 10 7 1 22336 0 0 2 5174 8 0 2 81582 5 1 0 3258 3 1 0 19250 0 0 0 40 5 0 0 24725 8 1 2 15000 17 0 2 117851 9 8 1 0 0 0 1 23361 8 8 1 524112 21 13 1 62599 8 4 1 20000 9 7 1 2000 21 1 1 15230 13 9 1 29505 0 0 0 1000 8 0 0 32000 5 2 1 7000 0 1 1 17000 3 5 1 170963 14 2 0 0 0 0 0 12702 7 2 1 7349 8 2 1 1000 40 0 0 20148 8 2 2 15790 6 4 2 102565 10 5 1 36000 25 0 0 18000 1 5 1 95000 44 0 0 3000 2 3 1 30000 60 0 0 1300 2 1 1 25572 3 3 1 130746 21 11 1 2846 7 1 1 30787 4 3 1 49000 0 5 1 994355 20 14 1 0 0 0 1 2000 60 1 1 8419 4 1 1 6198 70 0 0 0 0 0 0 6646 6 5 1 0 0 0 1 2800 10 1 1 2671079 48 59 1 81829 2 2 2 20792 5 2 2 100000 14 10 1 14560 2 8 1 50000 3 5 1 20949 8 7 1 11592 3 0 1 3200 0 0 0 215000 7 0 1 24736 5 2 1 7771 5 1 1 2954 0 0 1 21913 8 4 1 15586 10 2 1 10000 10 0 0 11919 2 0 0 15000 0 0 0 3000 2 1 0 0 8 0 1 45000 5 3 1 135200 9 11 1 55656 7 4 1 35000 2 2 1 4206 10 3 1 17237 0 0 2 3619 6 1 2 21502 4 3 1 23000 10 0 0 66607 8 7 1 27450 4 0 0 269 4 0 0 51052 4 0 1 1275 18 0 0 142069 24 16 1 115000 39 0 0
Names of X columns:
EqpDamg Speed CarsDer AccTypeDummy
Sample Range:
(leave blank to include all observations)
From:
To:
Column Number of Endogenous Series
(?)
Fixed Seasonal Effects
2
Do not include Seasonal Dummies
Include Seasonal Dummies
Type of Equation
3
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
par6 <- '12' par5 <- '' par4 <- '' par3 <- 'No Linear Trend' par2 <- 'Do not include Seasonal Dummies' par1 <- '1' library(lattice) library(lmtest) library(car) library(MASS) n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test mywarning <- '' par6 <- as.numeric(par6) if(is.na(par6)) { par6 <- 12 mywarning = 'Warning: you did not specify the seasonality. The seasonal period was set to s = 12.' } par1 <- as.numeric(par1) if(is.na(par1)) { par1 <- 1 mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.' } if (par4=='') par4 <- 0 par4 <- as.numeric(par4) if (!is.numeric(par4)) par4 <- 0 if (par5=='') par5 <- 0 par5 <- as.numeric(par5) if (!is.numeric(par5)) par5 <- 0 x <- na.omit(t(y)) k <- length(x[1,]) n <- length(x[,1]) x1 <- cbind(x[,par1], x[,1:k!=par1]) mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) colnames(x1) <- mycolnames #colnames(x)[par1] x <- x1 if (par3 == 'First Differences'){ (n <- n -1) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 } if (par3 == 'Seasonal Differences (s)'){ (n <- n - par6) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+par6,j] - x[i,j] } } x <- x2 } if (par3 == 'First and Seasonal Differences (s)'){ (n <- n -1) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 (n <- n - par6) x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep=''))) for (i in 1:n) { for (j in 1:k) { x2[i,j] <- x[i+par6,j] - x[i,j] } } x <- x2 } if(par4 > 0) { x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep=''))) for (i in 1:(n-par4)) { for (j in 1:par4) { x2[i,j] <- x[i+par4-j,par1] } } x <- cbind(x[(par4+1):n,], x2) n <- n - par4 } if(par5 > 0) { x2 <- array(0, dim=c(n-par5*par6,par5), dimnames=list(1:(n-par5*par6), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep=''))) for (i in 1:(n-par5*par6)) { for (j in 1:par5) { x2[i,j] <- x[i+par5*par6-j*par6,par1] } } x <- cbind(x[(par5*par6+1):n,], x2) n <- n - par5*par6 } if (par2 == 'Include Seasonal Dummies'){ x2 <- array(0, dim=c(n,par6-1), dimnames=list(1:n, paste('M', seq(1:(par6-1)), sep =''))) for (i in 1:(par6-1)){ x2[seq(i,n,par6),i] <- 1 } x <- cbind(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[n,])) if (par3 == 'Linear Trend'){ x <- cbind(x, c(1:n)) colnames(x)[k+1] <- 't' } print(x) (k <- length(x[n,])) head(x) 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$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() bitmap(file='test2.png') sresid <- studres(mylm) hist(sresid, freq=FALSE, main='Distribution of Studentized Residuals') xfit<-seq(min(sresid),max(sresid),length=40) yfit<-dnorm(xfit) lines(xfit, yfit) grid() dev.off() bitmap(file='test3.png') densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() bitmap(file='test4.png') qqPlot(mylm, main='QQ Plot') grid() dev.off() (myerror <- as.ts(mysum$resid)) bitmap(file='test5.png') dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) print(z) plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') lines(lowess(z)) abline(lm(z)) grid() dev.off() bitmap(file='test6.png') acf(mysum$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, signif(mysum$coefficients[i,1],6), sep=' ') if (rownames(mysum$coefficients)[i] != '(Intercept)') { myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, mywarning) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'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$coefficients)[i],header=TRUE) a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+')) a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+')) a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='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,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'R-squared',1,TRUE) a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-squared',1,TRUE) a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (value)',1,TRUE) a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) a<-table.element(a, signif(mysum$fstatistic[2],6)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) a<-table.element(a, signif(mysum$fstatistic[3],6)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'p-value',1,TRUE) a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Standard Deviation',1,TRUE) a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' ')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' ')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') myr <- as.numeric(mysum$resid) myr a <-table.start() a <- table.row.start(a) a <- table.element(a,'Menu of Residual Diagnostics',2,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Description',1,TRUE) a <- table.element(a,'Link',1,TRUE) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Histogram',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_histogram.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_centraltendency.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'QQ Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_fitdistrnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Kernel Density Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_density.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Skewness/Kurtosis Test',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Skewness-Kurtosis Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis_plot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Harrell-Davis Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_harrell_davis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Bootstrap Plot -- Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Blocked Bootstrap Plot -- Central Tendency',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'(Partial) Autocorrelation Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_autocorrelation.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Spectral Analysis',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_spectrum.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Tukey lambda PPCC Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_tukeylambda.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <-table.element(a,'Box-Cox Normality Plot',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_boxcoxnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a <- table.row.start(a) a <- table.element(a,'Summary Statistics',1,header=TRUE) a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_summary1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1) a <- table.row.end(a) a<-table.end(a) table.save(a,file='mytable7.tab') if(n < 200) { a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE) a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' ')) a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' ')) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='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,signif(numsignificant1,6)) a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' ')) if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'5% type I error level',header=TRUE) a<-table.element(a,signif(numsignificant5,6)) a<-table.element(a,signif(numsignificant5/numgqtests,6)) if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'10% type I error level',header=TRUE) a<-table.element(a,signif(numsignificant10,6)) a<-table.element(a,signif(numsignificant10/numgqtests,6)) if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable6.tab') } } a<-table.start() a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of fitted values',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_fitted <- resettest(mylm,power=2:3,type='fitted') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_fitted'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of regressors',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_regressors <- resettest(mylm,power=2:3,type='regressor') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_regressors'),'</pre>',sep='')) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of principal components',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) reset_test_principal_components <- resettest(mylm,power=2:3,type='princomp') a<-table.element(a,paste('<pre>',RC.texteval('reset_test_principal_components'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable8.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Variance Inflation Factors (Multicollinearity)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) vif <- vif(mylm) a<-table.element(a,paste('<pre>',RC.texteval('vif'),'</pre>',sep='')) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable9.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation