R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 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(162556 + ,807 + ,213118 + ,6282154 + ,29790 + ,444 + ,81767 + ,4321023 + ,87550 + ,412 + ,153198 + ,4111912 + ,84738 + ,428 + ,-26007 + ,223193 + ,54660 + ,315 + ,126942 + ,1491348 + ,42634 + ,168 + ,157214 + ,1629616 + ,40949 + ,263 + ,129352 + ,1398893 + ,45187 + ,267 + ,234817 + ,1926517 + ,37704 + ,228 + ,60448 + ,983660 + ,16275 + ,129 + ,47818 + ,1443586 + ,25830 + ,104 + ,245546 + ,1073089 + ,12679 + ,122 + ,48020 + ,984885 + ,18014 + ,393 + ,-1710 + ,1405225 + ,43556 + ,190 + ,32648 + ,227132 + ,24811 + ,280 + ,95350 + ,929118 + ,6575 + ,63 + ,151352 + ,1071292 + ,7123 + ,102 + ,288170 + ,638830 + ,21950 + ,265 + ,114337 + ,856956 + ,37597 + ,234 + ,37884 + ,992426 + ,17821 + ,277 + ,122844 + ,444477 + ,12988 + ,73 + ,82340 + ,857217 + ,22330 + ,67 + ,79801 + ,711969 + ,13326 + ,103 + ,165548 + ,702380 + ,16189 + ,290 + ,116384 + ,358589 + ,7146 + ,83 + ,134028 + ,297978 + ,15824 + ,56 + ,63838 + ,585715 + ,27664 + ,236 + ,74996 + ,657954 + ,11920 + ,73 + ,31080 + ,209458 + ,8568 + ,34 + ,32168 + ,786690 + ,14416 + ,139 + ,49857 + ,439798 + ,3369 + ,26 + ,87161 + ,688779 + ,11819 + ,70 + ,106113 + ,574339 + ,6984 + ,40 + ,80570 + ,741409 + ,4519 + ,42 + ,102129 + ,597793 + ,2220 + ,12 + ,301670 + ,644190 + ,18562 + ,211 + ,102313 + ,377934 + ,10327 + ,74 + ,88577 + ,640273 + ,5336 + ,80 + ,112477 + ,697458 + ,2365 + ,83 + ,191778 + ,550608 + ,4069 + ,131 + ,79804 + ,207393 + ,8636 + ,203 + ,128294 + ,301607 + ,13718 + ,56 + ,96448 + ,345783 + ,4525 + ,89 + ,93811 + ,501749 + ,6869 + ,88 + ,117520 + ,379983 + ,4628 + ,39 + ,69159 + ,387475 + ,3689 + ,25 + ,101792 + ,377305 + ,4891 + ,49 + ,210568 + ,370837 + ,7489 + ,149 + ,136996 + ,430866 + ,4901 + ,58 + ,121920 + ,469107 + ,2284 + ,41 + ,76403 + ,194493 + ,3160 + ,90 + ,108094 + ,530670 + ,4150 + ,136 + ,134759 + ,518365 + ,7285 + ,97 + ,188873 + ,491303 + ,1134 + ,63 + ,146216 + ,527021 + ,4658 + ,114 + ,156608 + ,233773 + ,2384 + ,77 + ,61348 + ,405972 + ,3748 + ,6 + ,50350 + ,652925 + ,5371 + ,47 + ,87720 + ,446211 + ,1285 + ,51 + ,99489 + ,341340 + ,9327 + ,85 + ,87419 + ,387699 + ,5565 + ,43 + ,94355 + ,493408 + ,1528 + ,32 + ,60326 + ,146494 + ,3122 + ,25 + ,94670 + ,414462 + ,7561 + ,77 + ,82425 + ,364304 + ,2675 + ,54 + ,59017 + ,355178 + ,13253 + ,251 + ,90829 + ,357760 + ,880 + ,15 + ,80791 + ,261216 + ,2053 + ,44 + ,100423 + ,397144 + ,1424 + ,73 + ,131116 + ,374943 + ,4036 + ,85 + ,100269 + ,424898 + ,3045 + ,49 + ,27330 + ,202055 + ,5119 + ,38 + ,39039 + ,378525 + ,1431 + ,35 + ,106885 + ,310768 + ,554 + ,9 + ,79285 + ,325738 + ,1975 + ,34 + ,118881 + ,394510 + ,1765 + ,20 + ,77623 + ,247060 + ,1012 + ,29 + ,114768 + ,368078 + ,810 + ,11 + ,74015 + ,236761 + ,1280 + ,52 + ,69465 + ,312378 + ,666 + ,13 + ,117869 + ,339836 + ,1380 + ,29 + ,60982 + ,347385 + ,4677 + ,66 + ,90131 + ,426280 + ,876 + ,33 + ,138971 + ,352850 + ,814 + ,15 + ,39625 + ,301881 + ,514 + ,15 + ,102725 + ,377516 + ,5692 + ,68 + ,64239 + ,357312 + ,3642 + ,100 + ,90262 + ,458343 + ,540 + ,13 + ,103960 + ,354228 + ,2099 + ,45 + ,106611 + ,308636 + ,567 + ,14 + ,103345 + ,386212 + ,2001 + ,36 + ,95551 + ,393343 + ,2949 + ,40 + ,82903 + ,378509 + ,2253 + ,68 + ,63593 + ,452469 + ,6533 + ,29 + ,126910 + ,364839 + ,1889 + ,43 + ,37527 + ,358649 + ,3055 + ,30 + ,60247 + ,376641 + ,272 + ,9 + ,112995 + ,429112 + ,1414 + ,22 + ,70184 + ,330546 + ,2564 + ,19 + ,130140 + ,403560 + ,1383 + ,9 + ,73221 + ,317892 + ,1261 + ,31 + ,76114 + ,307528 + ,975 + ,19 + ,90534 + ,235133 + ,3366 + ,55 + ,108479 + ,299243 + ,576 + ,8 + ,113761 + ,314073 + ,1686 + ,28 + ,68696 + ,368186 + ,746 + ,29 + ,71561 + ,269661 + ,3192 + ,48 + ,59831 + ,125390 + ,2045 + ,16 + ,97890 + ,510834 + ,5702 + ,47 + ,101481 + ,321896 + ,1932 + ,20 + ,72954 + ,249898 + ,936 + ,22 + ,67939 + ,408881 + ,3437 + ,33 + ,48022 + ,158492 + ,5131 + ,44 + ,86111 + ,292154 + ,2397 + ,13 + ,74020 + ,289513 + ,1389 + ,6 + ,57530 + ,378049 + ,1503 + ,35 + ,56364 + ,343466 + ,402 + ,8 + ,84990 + ,332743 + ,2239 + ,17 + ,88590 + ,442882 + ,2234 + ,11 + ,77200 + ,214215 + ,837 + ,21 + ,61262 + ,315688 + ,10579 + ,92 + ,110309 + ,375195 + ,875 + ,12 + ,67000 + ,334280 + ,1585 + ,112 + ,93099 + ,355864 + ,1659 + ,25 + ,107577 + ,480382 + ,2647 + ,17 + ,62920 + ,353058 + ,3294 + ,23 + ,75832 + ,217193 + ,0 + ,0 + ,60720 + ,315380 + ,94 + ,10 + ,60793 + ,314533 + ,422 + ,23 + ,57935 + ,318056 + ,0 + ,0 + ,60720 + ,315380 + ,34 + ,7 + ,60630 + ,314353 + ,1558 + ,25 + ,55637 + ,369448 + ,0 + ,1 + ,60720 + ,315380 + ,43 + ,20 + ,60887 + ,312846 + ,645 + ,4 + ,60720 + ,312075 + ,316 + ,4 + ,60505 + ,315009 + ,115 + ,10 + ,60945 + ,318903 + ,5 + ,1 + ,60720 + ,314887 + ,897 + ,4 + ,60720 + ,314913 + ,0 + ,0 + ,60720 + ,315380 + ,389 + ,8 + ,58990 + ,325506 + ,0 + ,0 + ,60720 + ,315380 + ,1002 + ,11 + ,56750 + ,298568 + ,36 + ,4 + ,60894 + ,315834 + ,460 + ,15 + ,63346 + ,329784 + ,309 + ,9 + ,56535 + ,312878 + ,0 + ,0 + ,60720 + ,315380 + ,9 + ,7 + ,60835 + ,314987 + ,271 + ,2 + ,60720 + ,325249 + ,14 + ,0 + ,61016 + ,315877 + ,520 + ,7 + ,58650 + ,291650 + ,1766 + ,46 + ,60438 + ,305959 + ,0 + ,5 + ,60720 + ,315380 + ,458 + ,7 + ,58625 + ,297765 + ,20 + ,2 + ,60938 + ,315245 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,98 + ,2 + ,61490 + ,315236 + ,405 + ,5 + ,60845 + ,336425 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,483 + ,7 + ,60830 + ,306268 + ,454 + ,24 + ,63261 + ,302187 + ,47 + ,1 + ,60720 + ,314882 + ,0 + ,0 + ,60720 + ,315380 + ,757 + ,18 + ,45689 + ,382712 + ,4655 + ,55 + ,60720 + ,341570 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,36 + ,3 + ,61564 + ,312412 + ,0 + ,0 + ,60720 + ,315380 + ,203 + ,9 + ,61938 + ,309596 + ,0 + ,0 + ,60720 + ,315380 + ,126 + ,8 + ,60951 + ,315547 + ,400 + ,113 + ,60720 + ,313267 + ,71 + ,0 + ,60745 + ,316176 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,972 + ,19 + ,71642 + ,359335 + ,531 + ,11 + ,71641 + ,330068 + ,2461 + ,25 + ,55792 + ,314289 + ,378 + ,16 + ,71873 + ,297413 + ,23 + ,5 + ,62555 + ,314806 + ,638 + ,11 + ,60370 + ,333210 + ,2300 + ,23 + ,64873 + ,352108 + ,149 + ,6 + ,62041 + ,313332 + ,226 + ,5 + ,65745 + ,291787 + ,0 + ,0 + ,60720 + ,315380 + ,275 + ,7 + ,59500 + ,318745 + ,0 + ,0 + ,60720 + ,315380 + ,141 + ,7 + ,61630 + ,315366 + ,0 + ,0 + ,60720 + ,315380 + ,28 + ,3 + ,60890 + ,315688 + ,0 + ,0 + ,60720 + ,315380 + ,4980 + ,89 + ,113521 + ,409642 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,472 + ,19 + ,80045 + ,269587 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,203 + ,12 + ,50804 + ,300962 + ,496 + ,12 + ,87390 + ,325479 + ,10 + ,5 + ,61656 + ,316155 + ,63 + ,2 + ,65688 + ,318574 + ,0 + ,0 + ,60720 + ,315380 + ,1136 + ,26 + ,48522 + ,343613 + ,265 + ,3 + ,60720 + ,306948 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,267 + ,11 + ,57640 + ,330059 + ,474 + ,10 + ,61977 + ,288985 + ,534 + ,5 + ,62620 + ,304485 + ,0 + ,2 + ,60720 + ,315380 + ,15 + ,6 + ,60831 + ,315688 + ,397 + ,7 + ,60646 + ,317736 + ,0 + ,2 + ,60720 + ,315380 + ,1866 + ,28 + ,56225 + ,322331 + ,288 + ,3 + ,60510 + ,296656 + ,0 + ,0 + ,60720 + ,315380 + ,3 + ,1 + ,60698 + ,315354 + ,468 + ,20 + ,60720 + ,312161 + ,20 + ,1 + ,60805 + ,315576 + ,278 + ,22 + ,61404 + ,314922 + ,61 + ,9 + ,60720 + ,314551 + ,0 + ,0 + ,60720 + ,315380 + ,192 + ,2 + ,65276 + ,312339 + ,0 + ,0 + ,60720 + ,315380 + ,317 + ,7 + ,63915 + ,298700 + ,738 + ,9 + ,60720 + ,321376 + ,0 + ,0 + ,60720 + ,315380 + ,368 + ,13 + ,61686 + ,303230 + ,0 + ,0 + ,60720 + ,315380 + ,2 + ,0 + ,60743 + ,315487 + ,0 + ,0 + ,60720 + ,315380 + ,53 + ,6 + ,60349 + ,315793 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,94 + ,3 + ,61360 + ,312887 + ,0 + ,0 + ,60720 + ,315380 + ,24 + ,7 + ,59818 + ,315637 + ,2332 + ,2 + ,72680 + ,324385 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,131 + ,15 + ,61808 + ,308989 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,206 + ,9 + ,53110 + ,296702 + ,0 + ,0 + ,60720 + ,315380 + ,167 + ,1 + ,64245 + ,307322 + ,622 + ,38 + ,73007 + ,304376 + ,2328 + ,57 + ,82732 + ,253588 + ,0 + ,0 + ,60720 + ,315380 + ,365 + ,7 + ,54820 + ,309560 + ,364 + ,26 + ,47705 + ,298466 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,226 + ,13 + ,72835 + ,343929 + ,307 + ,10 + ,58856 + ,331955 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,188 + ,9 + ,77655 + ,381180 + ,0 + ,0 + ,60720 + ,315380 + ,138 + ,26 + ,69817 + ,331420 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,125 + ,19 + ,60798 + ,310201 + ,0 + ,0 + ,60720 + ,315380 + ,282 + ,12 + ,62452 + ,320016 + ,335 + ,23 + ,64175 + ,320398 + ,0 + ,0 + ,60720 + ,315380 + ,1324 + ,29 + ,67440 + ,291841 + ,176 + ,8 + ,68136 + ,310670 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,249 + ,26 + ,56726 + ,313491 + ,0 + ,0 + ,60720 + ,315380 + ,333 + ,9 + ,70811 + ,331323 + ,0 + ,0 + ,60720 + ,315380 + ,601 + ,5 + ,60720 + ,319210 + ,30 + ,3 + ,62045 + ,318098 + ,0 + ,0 + ,60720 + ,315380 + ,249 + ,13 + ,54323 + ,292754 + ,0 + ,0 + ,60720 + ,315380 + ,165 + ,12 + ,62841 + ,325176 + ,453 + ,19 + ,81125 + ,365959 + ,0 + ,0 + ,60720 + ,315380 + ,53 + ,10 + ,59506 + ,302409 + ,382 + ,9 + ,59365 + ,340968 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,9 + ,60720 + ,315380 + ,30 + ,4 + ,60798 + ,313164 + ,290 + ,1 + ,58790 + ,301164 + ,0 + ,1 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,366 + ,14 + ,61808 + ,344425 + ,2 + ,12 + ,60735 + ,315394 + ,0 + ,0 + ,60720 + ,315380 + ,209 + ,19 + ,64016 + ,316647 + ,384 + ,17 + ,54683 + ,309836 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,365 + ,32 + ,87192 + ,346611 + ,0 + ,0 + ,60720 + ,315380 + ,49 + ,14 + ,64107 + ,322031 + ,3 + ,8 + ,60761 + ,315656 + ,133 + ,4 + ,65990 + ,339445 + ,32 + ,0 + ,59988 + ,314964 + ,368 + ,20 + ,61167 + ,297141 + ,1 + ,5 + ,60719 + ,315372 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,22 + ,1 + ,60722 + ,312502 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,96 + ,4 + ,60379 + ,313729 + ,1 + ,1 + ,60727 + ,315388 + ,314 + ,4 + ,60720 + ,315371 + ,844 + ,20 + ,60925 + ,296139 + ,0 + ,0 + ,60720 + ,315380 + ,26 + ,1 + ,60896 + ,313880 + ,125 + ,10 + ,59734 + ,317698 + ,304 + ,12 + ,62969 + ,295580 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,621 + ,13 + ,60720 + ,308256 + ,0 + ,0 + ,60720 + ,315380 + ,119 + ,3 + ,59118 + ,303677 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,1595 + ,10 + ,60720 + ,319369 + ,312 + ,3 + ,58598 + ,318690 + ,60 + ,7 + ,61124 + ,314049 + ,587 + ,10 + ,59595 + ,325699 + ,135 + ,1 + ,62065 + ,314210 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,514 + ,15 + ,78780 + ,322378 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,1 + ,4 + ,60722 + ,315398 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,1763 + ,28 + ,61600 + ,308336 + ,180 + ,9 + ,59635 + ,316386 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,218 + ,7 + ,60720 + ,315553 + ,0 + ,0 + ,60720 + ,315380 + ,448 + ,7 + ,59781 + ,323361 + ,227 + ,7 + ,76644 + ,336639 + ,174 + ,3 + ,64820 + ,307424 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,121 + ,11 + ,56178 + ,295370 + ,607 + ,7 + ,60436 + ,322340 + ,2212 + ,10 + ,60720 + ,319864 + ,0 + ,0 + ,60720 + ,315380 + ,0 + ,0 + ,60720 + ,315380 + ,530 + ,18 + ,73433 + ,317291 + ,571 + ,14 + ,41477 + ,280398 + ,0 + ,0 + ,60720 + ,315380 + ,78 + ,12 + ,62700 + ,317330 + ,2489 + ,29 + ,67804 + ,238125 + ,131 + ,3 + ,59661 + ,327071 + ,923 + ,6 + ,58620 + ,309038 + ,72 + ,3 + ,60398 + ,314210 + ,572 + ,8 + ,58580 + ,307930 + ,397 + ,10 + ,62710 + ,322327 + ,450 + ,6 + ,59325 + ,292136 + ,622 + ,8 + ,60950 + ,263276 + ,694 + ,6 + ,68060 + ,367655 + ,3425 + ,9 + ,83620 + ,283910 + ,562 + ,8 + ,58456 + ,283587 + ,4917 + ,26 + ,52811 + ,243650 + ,1442 + ,239 + ,121173 + ,438493 + ,529 + ,7 + ,63870 + ,296261 + ,2126 + ,41 + ,21001 + ,230621 + ,1061 + ,3 + ,70415 + ,304252 + ,776 + ,8 + ,64230 + ,333505 + ,611 + ,6 + ,59190 + ,296919 + ,1526 + ,21 + ,69351 + ,278990 + ,592 + ,7 + ,64270 + ,276898 + ,1182 + ,11 + ,70694 + ,327007 + ,621 + ,11 + ,68005 + ,317046 + ,989 + ,12 + ,58930 + ,304555 + ,438 + ,9 + ,58320 + ,298096 + ,726 + ,3 + ,69980 + ,231861 + ,1303 + ,57 + ,69863 + ,309422 + ,7419 + ,21 + ,63255 + ,286963 + ,1164 + ,15 + ,57320 + ,269753 + ,3310 + ,32 + ,75230 + ,448243 + ,1920 + ,11 + ,79420 + ,165404 + ,965 + ,2 + ,73490 + ,204325 + ,3256 + ,23 + ,35250 + ,407159 + ,1135 + ,20 + ,62285 + ,290476 + ,1270 + ,24 + ,69206 + ,275311 + ,661 + ,1 + ,65920 + ,246541 + ,1013 + ,1 + ,69770 + ,253468 + ,2844 + ,74 + ,72683 + ,240897 + ,11528 + ,68 + ,-14545 + ,-83265 + ,6526 + ,20 + ,55830 + ,-42143 + ,2264 + ,20 + ,55174 + ,272713 + ,5109 + ,82 + ,67038 + ,215362 + ,3999 + ,21 + ,51252 + ,42754 + ,35624 + ,244 + ,157278 + ,306275 + ,9252 + ,32 + ,79510 + ,253537 + ,15236 + ,86 + ,77440 + ,372631 + ,18073 + ,69 + ,27284 + ,-7170) + ,dim=c(4 + ,431) + ,dimnames=list(c('Costs' + ,'Orders' + ,'Dividends' + ,'Wealth') + ,1:431)) > y <- array(NA,dim=c(4,431),dimnames=list(c('Costs','Orders','Dividends','Wealth'),1:431)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'no' > par3 = '3' > par2 = 'none' > par1 = '3' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, 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: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Dividends" > x[,par1] [1] 213118 81767 153198 -26007 126942 157214 129352 234817 60448 47818 [11] 245546 48020 -1710 32648 95350 151352 288170 114337 37884 122844 [21] 82340 79801 165548 116384 134028 63838 74996 31080 32168 49857 [31] 87161 106113 80570 102129 301670 102313 88577 112477 191778 79804 [41] 128294 96448 93811 117520 69159 101792 210568 136996 121920 76403 [51] 108094 134759 188873 146216 156608 61348 50350 87720 99489 87419 [61] 94355 60326 94670 82425 59017 90829 80791 100423 131116 100269 [71] 27330 39039 106885 79285 118881 77623 114768 74015 69465 117869 [81] 60982 90131 138971 39625 102725 64239 90262 103960 106611 103345 [91] 95551 82903 63593 126910 37527 60247 112995 70184 130140 73221 [101] 76114 90534 108479 113761 68696 71561 59831 97890 101481 72954 [111] 67939 48022 86111 74020 57530 56364 84990 88590 77200 61262 [121] 110309 67000 93099 107577 62920 75832 60720 60793 57935 60720 [131] 60630 55637 60720 60887 60720 60505 60945 60720 60720 60720 [141] 58990 60720 56750 60894 63346 56535 60720 60835 60720 61016 [151] 58650 60438 60720 58625 60938 60720 60720 61490 60845 60720 [161] 60720 60720 60720 60830 63261 60720 60720 45689 60720 60720 [171] 60720 61564 60720 61938 60720 60951 60720 60745 60720 60720 [181] 71642 71641 55792 71873 62555 60370 64873 62041 65745 60720 [191] 59500 60720 61630 60720 60890 60720 113521 60720 60720 80045 [201] 60720 60720 60720 50804 87390 61656 65688 60720 48522 60720 [211] 60720 60720 57640 61977 62620 60720 60831 60646 60720 56225 [221] 60510 60720 60698 60720 60805 61404 60720 60720 65276 60720 [231] 63915 60720 60720 61686 60720 60743 60720 60349 60720 60720 [241] 60720 61360 60720 59818 72680 60720 60720 61808 60720 60720 [251] 53110 60720 64245 73007 82732 60720 54820 47705 60720 60720 [261] 60720 60720 72835 58856 60720 60720 60720 77655 60720 69817 [271] 60720 60720 60720 60798 60720 62452 64175 60720 67440 68136 [281] 60720 60720 56726 60720 70811 60720 60720 62045 60720 54323 [291] 60720 62841 81125 60720 59506 59365 60720 60720 60720 60720 [301] 60798 58790 60720 60720 61808 60735 60720 64016 54683 60720 [311] 60720 87192 60720 64107 60761 65990 59988 61167 60719 60720 [321] 60720 60720 60720 60720 60720 60722 60720 60720 60720 60720 [331] 60720 60720 60720 60379 60727 60720 60925 60720 60896 59734 [341] 62969 60720 60720 60720 60720 60720 59118 60720 60720 60720 [351] 58598 61124 59595 62065 60720 60720 78780 60720 60720 60720 [361] 60722 60720 60720 61600 59635 60720 60720 60720 60720 60720 [371] 60720 59781 76644 64820 60720 60720 56178 60436 60720 60720 [381] 60720 73433 41477 60720 62700 67804 59661 58620 60398 58580 [391] 62710 59325 60950 68060 83620 58456 52811 121173 63870 21001 [401] 70415 64230 59190 69351 64270 70694 68005 58930 58320 69980 [411] 69863 63255 57320 75230 79420 73490 35250 62285 69206 65920 [421] 69770 72683 -14545 55830 55174 67038 51252 157278 79510 77440 [431] 27284 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) -26007 -14545 -1710 21001 27284 27330 31080 32168 32648 35250 37527 1 1 1 1 1 1 1 1 1 1 1 37884 39039 39625 41477 45689 47705 47818 48020 48022 48522 49857 1 1 1 1 1 1 1 1 1 1 1 50350 50804 51252 52811 53110 54323 54683 54820 55174 55637 55792 1 1 1 1 1 1 1 1 1 1 1 55830 56178 56225 56364 56535 56726 56750 57320 57530 57640 57935 1 1 1 1 1 1 1 1 1 1 1 58320 58456 58580 58598 58620 58625 58650 58790 58856 58930 58990 1 1 1 1 1 1 1 1 1 1 1 59017 59118 59190 59325 59365 59500 59506 59595 59635 59661 59734 1 1 1 1 1 1 1 1 1 1 1 59781 59818 59831 59988 60247 60326 60349 60370 60379 60398 60436 1 1 1 1 1 1 1 1 1 1 1 60438 60448 60505 60510 60630 60646 60698 60719 60720 60722 60727 1 1 1 1 1 1 1 1 134 2 1 60735 60743 60745 60761 60793 60798 60805 60830 60831 60835 60845 1 1 1 1 1 2 1 1 1 1 1 60887 60890 60894 60896 60925 60938 60945 60950 60951 60982 61016 1 1 1 1 1 1 1 1 1 1 1 61124 61167 61262 61348 61360 61404 61490 61564 61600 61630 61656 1 1 1 1 1 1 1 1 1 1 1 61686 61808 61938 61977 62041 62045 62065 62285 62452 62555 62620 1 2 1 1 1 1 1 1 1 1 1 62700 62710 62841 62920 62969 63255 63261 63346 63593 63838 63870 1 1 1 1 1 1 1 1 1 1 1 63915 64016 64107 64175 64230 64239 64245 64270 64820 64873 65276 1 1 1 1 1 1 1 1 1 1 1 65688 65745 65920 65990 67000 67038 67440 67804 67939 68005 68060 1 1 1 1 1 1 1 1 1 1 1 68136 68696 69159 69206 69351 69465 69770 69817 69863 69980 70184 1 1 1 1 1 1 1 1 1 1 1 70415 70694 70811 71561 71641 71642 71873 72680 72683 72835 72954 1 1 1 1 1 1 1 1 1 1 1 73007 73221 73433 73490 74015 74020 74996 75230 75832 76114 76403 1 1 1 1 1 1 1 1 1 1 1 76644 77200 77440 77623 77655 78780 79285 79420 79510 79801 79804 1 1 1 1 1 1 1 1 1 1 1 80045 80570 80791 81125 81767 82340 82425 82732 82903 83620 84990 1 1 1 1 1 1 1 1 1 1 1 86111 87161 87192 87390 87419 87720 88577 88590 90131 90262 90534 1 1 1 1 1 1 1 1 1 1 1 90829 93099 93811 94355 94670 95350 95551 96448 97890 99489 100269 1 1 1 1 1 1 1 1 1 1 1 100423 101481 101792 102129 102313 102725 103345 103960 106113 106611 106885 1 1 1 1 1 1 1 1 1 1 1 107577 108094 108479 110309 112477 112995 113521 113761 114337 114768 116384 1 1 1 1 1 1 1 1 1 1 1 117520 117869 118881 121173 121920 122844 126910 126942 128294 129352 130140 1 1 1 1 1 1 1 1 1 1 1 131116 134028 134759 136996 138971 146216 151352 153198 156608 157214 157278 1 1 1 1 1 1 1 1 1 1 1 165548 188873 191778 210568 213118 234817 245546 288170 301670 1 1 1 1 1 1 1 1 1 > colnames(x) [1] "Costs" "Orders" "Dividends" "Wealth" > colnames(x)[par1] [1] "Dividends" > x[,par1] [1] 213118 81767 153198 -26007 126942 157214 129352 234817 60448 47818 [11] 245546 48020 -1710 32648 95350 151352 288170 114337 37884 122844 [21] 82340 79801 165548 116384 134028 63838 74996 31080 32168 49857 [31] 87161 106113 80570 102129 301670 102313 88577 112477 191778 79804 [41] 128294 96448 93811 117520 69159 101792 210568 136996 121920 76403 [51] 108094 134759 188873 146216 156608 61348 50350 87720 99489 87419 [61] 94355 60326 94670 82425 59017 90829 80791 100423 131116 100269 [71] 27330 39039 106885 79285 118881 77623 114768 74015 69465 117869 [81] 60982 90131 138971 39625 102725 64239 90262 103960 106611 103345 [91] 95551 82903 63593 126910 37527 60247 112995 70184 130140 73221 [101] 76114 90534 108479 113761 68696 71561 59831 97890 101481 72954 [111] 67939 48022 86111 74020 57530 56364 84990 88590 77200 61262 [121] 110309 67000 93099 107577 62920 75832 60720 60793 57935 60720 [131] 60630 55637 60720 60887 60720 60505 60945 60720 60720 60720 [141] 58990 60720 56750 60894 63346 56535 60720 60835 60720 61016 [151] 58650 60438 60720 58625 60938 60720 60720 61490 60845 60720 [161] 60720 60720 60720 60830 63261 60720 60720 45689 60720 60720 [171] 60720 61564 60720 61938 60720 60951 60720 60745 60720 60720 [181] 71642 71641 55792 71873 62555 60370 64873 62041 65745 60720 [191] 59500 60720 61630 60720 60890 60720 113521 60720 60720 80045 [201] 60720 60720 60720 50804 87390 61656 65688 60720 48522 60720 [211] 60720 60720 57640 61977 62620 60720 60831 60646 60720 56225 [221] 60510 60720 60698 60720 60805 61404 60720 60720 65276 60720 [231] 63915 60720 60720 61686 60720 60743 60720 60349 60720 60720 [241] 60720 61360 60720 59818 72680 60720 60720 61808 60720 60720 [251] 53110 60720 64245 73007 82732 60720 54820 47705 60720 60720 [261] 60720 60720 72835 58856 60720 60720 60720 77655 60720 69817 [271] 60720 60720 60720 60798 60720 62452 64175 60720 67440 68136 [281] 60720 60720 56726 60720 70811 60720 60720 62045 60720 54323 [291] 60720 62841 81125 60720 59506 59365 60720 60720 60720 60720 [301] 60798 58790 60720 60720 61808 60735 60720 64016 54683 60720 [311] 60720 87192 60720 64107 60761 65990 59988 61167 60719 60720 [321] 60720 60720 60720 60720 60720 60722 60720 60720 60720 60720 [331] 60720 60720 60720 60379 60727 60720 60925 60720 60896 59734 [341] 62969 60720 60720 60720 60720 60720 59118 60720 60720 60720 [351] 58598 61124 59595 62065 60720 60720 78780 60720 60720 60720 [361] 60722 60720 60720 61600 59635 60720 60720 60720 60720 60720 [371] 60720 59781 76644 64820 60720 60720 56178 60436 60720 60720 [381] 60720 73433 41477 60720 62700 67804 59661 58620 60398 58580 [391] 62710 59325 60950 68060 83620 58456 52811 121173 63870 21001 [401] 70415 64230 59190 69351 64270 70694 68005 58930 58320 69980 [411] 69863 63255 57320 75230 79420 73490 35250 62285 69206 65920 [421] 69770 72683 -14545 55830 55174 67038 51252 157278 79510 77440 [431] 27284 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/191ua1292939322.tab") + } + } > m Conditional inference tree with 8 terminal nodes Response: Dividends Inputs: Costs, Orders, Wealth Number of observations: 431 1) Orders <= 82; criterion = 1, statistic = 61.482 2) Wealth <= 359335; criterion = 1, statistic = 74.707 3) Wealth <= 158492; criterion = 1, statistic = 26.863 4)* weights = 7 3) Wealth > 158492 5) Orders <= 29; criterion = 1, statistic = 21.989 6) Costs <= 468; criterion = 1, statistic = 14.486 7) Wealth <= 330059; criterion = 1, statistic = 33.308 8) Wealth <= 301164; criterion = 0.962, statistic = 6.201 9)* weights = 15 8) Wealth > 301164 10)* weights = 199 7) Wealth > 330059 11)* weights = 10 6) Costs > 468 12)* weights = 76 5) Orders > 29 13)* weights = 27 2) Wealth > 359335 14)* weights = 51 1) Orders > 82 15)* weights = 46 > postscript(file="/var/www/html/rcomp/tmp/291ua1292939322.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/391ua1292939322.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } Actuals Forecasts Residuals 1 213118 113994.30 99123.69565 2 81767 113994.30 -32227.30435 3 153198 113994.30 39203.69565 4 -26007 113994.30 -140001.30435 5 126942 113994.30 12947.69565 6 157214 113994.30 43219.69565 7 129352 113994.30 15357.69565 8 234817 113994.30 120822.69565 9 60448 113994.30 -53546.30435 10 47818 113994.30 -66176.30435 11 245546 113994.30 131551.69565 12 48020 113994.30 -65974.30435 13 -1710 113994.30 -115704.30435 14 32648 113994.30 -81346.30435 15 95350 113994.30 -18644.30435 16 151352 94281.45 57070.54902 17 288170 113994.30 174175.69565 18 114337 113994.30 342.69565 19 37884 113994.30 -76110.30435 20 122844 113994.30 8849.69565 21 82340 94281.45 -11941.45098 22 79801 94281.45 -14480.45098 23 165548 113994.30 51553.69565 24 116384 113994.30 2389.69565 25 134028 113994.30 20033.69565 26 63838 94281.45 -30443.45098 27 74996 113994.30 -38998.30435 28 31080 74674.00 -43594.00000 29 32168 94281.45 -62113.45098 30 49857 113994.30 -64137.30435 31 87161 94281.45 -7120.45098 32 106113 94281.45 11831.54902 33 80570 94281.45 -13711.45098 34 102129 94281.45 7847.54902 35 301670 94281.45 207388.54902 36 102313 113994.30 -11681.30435 37 88577 94281.45 -5704.45098 38 112477 94281.45 18195.54902 39 191778 113994.30 77783.69565 40 79804 113994.30 -34190.30435 41 128294 113994.30 14299.69565 42 96448 74674.00 21774.00000 43 93811 113994.30 -20183.30435 44 117520 113994.30 3525.69565 45 69159 94281.45 -25122.45098 46 101792 94281.45 7510.54902 47 210568 94281.45 116286.54902 48 136996 113994.30 23001.69565 49 121920 94281.45 27638.54902 50 76403 74674.00 1729.00000 51 108094 113994.30 -5900.30435 52 134759 113994.30 20764.69565 53 188873 113994.30 74878.69565 54 146216 94281.45 51934.54902 55 156608 113994.30 42613.69565 56 61348 94281.45 -32933.45098 57 50350 94281.45 -43931.45098 58 87720 94281.45 -6561.45098 59 99489 74674.00 24815.00000 60 87419 113994.30 -26575.30435 61 94355 94281.45 73.54902 62 60326 41142.86 19183.14286 63 94670 94281.45 388.54902 64 82425 94281.45 -11856.45098 65 59017 74674.00 -15657.00000 66 90829 113994.30 -23165.30435 67 80791 67617.74 13173.26316 68 100423 94281.45 6141.54902 69 131116 94281.45 36834.54902 70 100269 113994.30 -13725.30435 71 27330 74674.00 -47344.00000 72 39039 94281.45 -55242.45098 73 106885 74674.00 32211.00000 74 79285 67617.74 11667.26316 75 118881 94281.45 24599.54902 76 77623 67617.74 10005.26316 77 114768 94281.45 20486.54902 78 74015 67617.74 6397.26316 79 69465 74674.00 -5209.00000 80 117869 67617.74 50251.26316 81 60982 67617.74 -6635.73684 82 90131 94281.45 -4150.45098 83 138971 74674.00 64297.00000 84 39625 67617.74 -27992.73684 85 102725 94281.45 8443.54902 86 64239 74674.00 -10435.00000 87 90262 113994.30 -23732.30435 88 103960 67617.74 36342.26316 89 106611 74674.00 31937.00000 90 103345 94281.45 9063.54902 91 95551 94281.45 1269.54902 92 82903 94281.45 -11378.45098 93 63593 94281.45 -30688.45098 94 126910 94281.45 32628.54902 95 37527 74674.00 -37147.00000 96 60247 94281.45 -34034.45098 97 112995 94281.45 18713.54902 98 70184 67617.74 2566.26316 99 130140 94281.45 35858.54902 100 73221 67617.74 5603.26316 101 76114 74674.00 1440.00000 102 90534 67617.74 22916.26316 103 108479 74674.00 33805.00000 104 113761 67617.74 46143.26316 105 68696 94281.45 -25585.45098 106 71561 67617.74 3943.26316 107 59831 41142.86 18688.14286 108 97890 94281.45 3608.54902 109 101481 74674.00 26807.00000 110 72954 67617.74 5336.26316 111 67939 94281.45 -26342.45098 112 48022 41142.86 6879.14286 113 86111 74674.00 11437.00000 114 74020 67617.74 6402.26316 115 57530 94281.45 -36751.45098 116 56364 74674.00 -18310.00000 117 84990 68196.10 16793.90000 118 88590 94281.45 -5691.45098 119 77200 67617.74 9582.26316 120 61262 67617.74 -6355.73684 121 110309 113994.30 -3685.30435 122 67000 67617.74 -617.73684 123 93099 113994.30 -20895.30435 124 107577 94281.45 13295.54902 125 62920 67617.74 -4697.73684 126 75832 67617.74 8214.26316 127 60720 60837.00 -117.00000 128 60793 60837.00 -44.00000 129 57935 60837.00 -2902.00000 130 60720 60837.00 -117.00000 131 60630 60837.00 -207.00000 132 55637 94281.45 -38644.45098 133 60720 60837.00 -117.00000 134 60887 60837.00 50.00000 135 60720 67617.74 -6897.73684 136 60505 60837.00 -332.00000 137 60945 60837.00 108.00000 138 60720 60837.00 -117.00000 139 60720 67617.74 -6897.73684 140 60720 60837.00 -117.00000 141 58990 60837.00 -1847.00000 142 60720 60837.00 -117.00000 143 56750 67617.74 -10867.73684 144 60894 60837.00 57.00000 145 63346 60837.00 2509.00000 146 56535 60837.00 -4302.00000 147 60720 60837.00 -117.00000 148 60835 60837.00 -2.00000 149 60720 60837.00 -117.00000 150 61016 60837.00 179.00000 151 58650 67617.74 -8967.73684 152 60438 74674.00 -14236.00000 153 60720 60837.00 -117.00000 154 58625 58890.60 -265.60000 155 60938 60837.00 101.00000 156 60720 60837.00 -117.00000 157 60720 60837.00 -117.00000 158 61490 60837.00 653.00000 159 60845 68196.10 -7351.10000 160 60720 60837.00 -117.00000 161 60720 60837.00 -117.00000 162 60720 60837.00 -117.00000 163 60720 60837.00 -117.00000 164 60830 67617.74 -6787.73684 165 63261 60837.00 2424.00000 166 60720 60837.00 -117.00000 167 60720 60837.00 -117.00000 168 45689 94281.45 -48592.45098 169 60720 74674.00 -13954.00000 170 60720 60837.00 -117.00000 171 60720 60837.00 -117.00000 172 61564 60837.00 727.00000 173 60720 60837.00 -117.00000 174 61938 60837.00 1101.00000 175 60720 60837.00 -117.00000 176 60951 60837.00 114.00000 177 60720 113994.30 -53274.30435 178 60745 60837.00 -92.00000 179 60720 60837.00 -117.00000 180 60720 60837.00 -117.00000 181 71642 67617.74 4024.26316 182 71641 67617.74 4023.26316 183 55792 67617.74 -11825.73684 184 71873 58890.60 12982.40000 185 62555 60837.00 1718.00000 186 60370 67617.74 -7247.73684 187 64873 67617.74 -2744.73684 188 62041 60837.00 1204.00000 189 65745 58890.60 6854.40000 190 60720 60837.00 -117.00000 191 59500 60837.00 -1337.00000 192 60720 60837.00 -117.00000 193 61630 60837.00 793.00000 194 60720 60837.00 -117.00000 195 60890 60837.00 53.00000 196 60720 60837.00 -117.00000 197 113521 113994.30 -473.30435 198 60720 60837.00 -117.00000 199 60720 60837.00 -117.00000 200 80045 67617.74 12427.26316 201 60720 60837.00 -117.00000 202 60720 60837.00 -117.00000 203 60720 60837.00 -117.00000 204 50804 58890.60 -8086.60000 205 87390 67617.74 19772.26316 206 61656 60837.00 819.00000 207 65688 60837.00 4851.00000 208 60720 60837.00 -117.00000 209 48522 67617.74 -19095.73684 210 60720 60837.00 -117.00000 211 60720 60837.00 -117.00000 212 60720 60837.00 -117.00000 213 57640 60837.00 -3197.00000 214 61977 67617.74 -5640.73684 215 62620 67617.74 -4997.73684 216 60720 60837.00 -117.00000 217 60831 60837.00 -6.00000 218 60646 60837.00 -191.00000 219 60720 60837.00 -117.00000 220 56225 67617.74 -11392.73684 221 60510 58890.60 1619.40000 222 60720 60837.00 -117.00000 223 60698 60837.00 -139.00000 224 60720 60837.00 -117.00000 225 60805 60837.00 -32.00000 226 61404 60837.00 567.00000 227 60720 60837.00 -117.00000 228 60720 60837.00 -117.00000 229 65276 60837.00 4439.00000 230 60720 60837.00 -117.00000 231 63915 58890.60 5024.40000 232 60720 67617.74 -6897.73684 233 60720 60837.00 -117.00000 234 61686 60837.00 849.00000 235 60720 60837.00 -117.00000 236 60743 60837.00 -94.00000 237 60720 60837.00 -117.00000 238 60349 60837.00 -488.00000 239 60720 60837.00 -117.00000 240 60720 60837.00 -117.00000 241 60720 60837.00 -117.00000 242 61360 60837.00 523.00000 243 60720 60837.00 -117.00000 244 59818 60837.00 -1019.00000 245 72680 67617.74 5062.26316 246 60720 60837.00 -117.00000 247 60720 60837.00 -117.00000 248 61808 60837.00 971.00000 249 60720 60837.00 -117.00000 250 60720 60837.00 -117.00000 251 53110 58890.60 -5780.60000 252 60720 60837.00 -117.00000 253 64245 60837.00 3408.00000 254 73007 74674.00 -1667.00000 255 82732 74674.00 8058.00000 256 60720 60837.00 -117.00000 257 54820 60837.00 -6017.00000 258 47705 58890.60 -11185.60000 259 60720 60837.00 -117.00000 260 60720 60837.00 -117.00000 261 60720 60837.00 -117.00000 262 60720 60837.00 -117.00000 263 72835 68196.10 4638.90000 264 58856 68196.10 -9340.10000 265 60720 60837.00 -117.00000 266 60720 60837.00 -117.00000 267 60720 60837.00 -117.00000 268 77655 94281.45 -16626.45098 269 60720 60837.00 -117.00000 270 69817 68196.10 1620.90000 271 60720 60837.00 -117.00000 272 60720 60837.00 -117.00000 273 60720 60837.00 -117.00000 274 60798 60837.00 -39.00000 275 60720 60837.00 -117.00000 276 62452 60837.00 1615.00000 277 64175 60837.00 3338.00000 278 60720 60837.00 -117.00000 279 67440 67617.74 -177.73684 280 68136 60837.00 7299.00000 281 60720 60837.00 -117.00000 282 60720 60837.00 -117.00000 283 56726 60837.00 -4111.00000 284 60720 60837.00 -117.00000 285 70811 68196.10 2614.90000 286 60720 60837.00 -117.00000 287 60720 67617.74 -6897.73684 288 62045 60837.00 1208.00000 289 60720 60837.00 -117.00000 290 54323 58890.60 -4567.60000 291 60720 60837.00 -117.00000 292 62841 60837.00 2004.00000 293 81125 94281.45 -13156.45098 294 60720 60837.00 -117.00000 295 59506 60837.00 -1331.00000 296 59365 68196.10 -8831.10000 297 60720 60837.00 -117.00000 298 60720 60837.00 -117.00000 299 60720 60837.00 -117.00000 300 60720 60837.00 -117.00000 301 60798 60837.00 -39.00000 302 58790 58890.60 -100.60000 303 60720 60837.00 -117.00000 304 60720 60837.00 -117.00000 305 61808 68196.10 -6388.10000 306 60735 60837.00 -102.00000 307 60720 60837.00 -117.00000 308 64016 60837.00 3179.00000 309 54683 60837.00 -6154.00000 310 60720 60837.00 -117.00000 311 60720 60837.00 -117.00000 312 87192 74674.00 12518.00000 313 60720 60837.00 -117.00000 314 64107 60837.00 3270.00000 315 60761 60837.00 -76.00000 316 65990 68196.10 -2206.10000 317 59988 60837.00 -849.00000 318 61167 58890.60 2276.40000 319 60719 60837.00 -118.00000 320 60720 60837.00 -117.00000 321 60720 60837.00 -117.00000 322 60720 60837.00 -117.00000 323 60720 60837.00 -117.00000 324 60720 60837.00 -117.00000 325 60720 60837.00 -117.00000 326 60722 60837.00 -115.00000 327 60720 60837.00 -117.00000 328 60720 60837.00 -117.00000 329 60720 60837.00 -117.00000 330 60720 60837.00 -117.00000 331 60720 60837.00 -117.00000 332 60720 60837.00 -117.00000 333 60720 60837.00 -117.00000 334 60379 60837.00 -458.00000 335 60727 60837.00 -110.00000 336 60720 60837.00 -117.00000 337 60925 67617.74 -6692.73684 338 60720 60837.00 -117.00000 339 60896 60837.00 59.00000 340 59734 60837.00 -1103.00000 341 62969 58890.60 4078.40000 342 60720 60837.00 -117.00000 343 60720 60837.00 -117.00000 344 60720 60837.00 -117.00000 345 60720 67617.74 -6897.73684 346 60720 60837.00 -117.00000 347 59118 60837.00 -1719.00000 348 60720 60837.00 -117.00000 349 60720 60837.00 -117.00000 350 60720 67617.74 -6897.73684 351 58598 60837.00 -2239.00000 352 61124 60837.00 287.00000 353 59595 67617.74 -8022.73684 354 62065 60837.00 1228.00000 355 60720 60837.00 -117.00000 356 60720 60837.00 -117.00000 357 78780 67617.74 11162.26316 358 60720 60837.00 -117.00000 359 60720 60837.00 -117.00000 360 60720 60837.00 -117.00000 361 60722 60837.00 -115.00000 362 60720 60837.00 -117.00000 363 60720 60837.00 -117.00000 364 61600 67617.74 -6017.73684 365 59635 60837.00 -1202.00000 366 60720 60837.00 -117.00000 367 60720 60837.00 -117.00000 368 60720 60837.00 -117.00000 369 60720 60837.00 -117.00000 370 60720 60837.00 -117.00000 371 60720 60837.00 -117.00000 372 59781 60837.00 -1056.00000 373 76644 68196.10 8447.90000 374 64820 60837.00 3983.00000 375 60720 60837.00 -117.00000 376 60720 60837.00 -117.00000 377 56178 58890.60 -2712.60000 378 60436 67617.74 -7181.73684 379 60720 67617.74 -6897.73684 380 60720 60837.00 -117.00000 381 60720 60837.00 -117.00000 382 73433 67617.74 5815.26316 383 41477 67617.74 -26140.73684 384 60720 60837.00 -117.00000 385 62700 60837.00 1863.00000 386 67804 67617.74 186.26316 387 59661 60837.00 -1176.00000 388 58620 67617.74 -8997.73684 389 60398 60837.00 -439.00000 390 58580 67617.74 -9037.73684 391 62710 60837.00 1873.00000 392 59325 58890.60 434.40000 393 60950 67617.74 -6667.73684 394 68060 94281.45 -26221.45098 395 83620 67617.74 16002.26316 396 58456 67617.74 -9161.73684 397 52811 67617.74 -14806.73684 398 121173 113994.30 7178.69565 399 63870 67617.74 -3747.73684 400 21001 74674.00 -53673.00000 401 70415 67617.74 2797.26316 402 64230 67617.74 -3387.73684 403 59190 67617.74 -8427.73684 404 69351 67617.74 1733.26316 405 64270 67617.74 -3347.73684 406 70694 67617.74 3076.26316 407 68005 67617.74 387.26316 408 58930 67617.74 -8687.73684 409 58320 58890.60 -570.60000 410 69980 67617.74 2362.26316 411 69863 74674.00 -4811.00000 412 63255 67617.74 -4362.73684 413 57320 67617.74 -10297.73684 414 75230 94281.45 -19051.45098 415 79420 67617.74 11802.26316 416 73490 67617.74 5872.26316 417 35250 94281.45 -59031.45098 418 62285 67617.74 -5332.73684 419 69206 67617.74 1588.26316 420 65920 67617.74 -1697.73684 421 69770 67617.74 2152.26316 422 72683 74674.00 -1991.00000 423 -14545 41142.86 -55687.85714 424 55830 41142.86 14687.14286 425 55174 67617.74 -12443.73684 426 67038 74674.00 -7636.00000 427 51252 41142.86 10109.14286 428 157278 113994.30 43283.69565 429 79510 74674.00 4836.00000 430 77440 113994.30 -36554.30435 431 27284 41142.86 -13858.85714 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/www/html/rcomp/tmp/4ckag1292939322.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/5y29l1292939322.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/6jk791292939322.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/7cc6c1292939322.tab") + } > > try(system("convert tmp/291ua1292939322.ps tmp/291ua1292939322.png",intern=TRUE)) character(0) > try(system("convert tmp/391ua1292939322.ps tmp/391ua1292939322.png",intern=TRUE)) character(0) > try(system("convert tmp/4ckag1292939322.ps tmp/4ckag1292939322.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.032 0.781 16.922