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RunMLogitTest.ox decl ml = new MLogit("Test","mlogit_example.dta","insure",
"age male nonwhite isite2 isite3");
ml->Estimate();
. webuse sysdsn1 (Health insurance data). mlogit insure age male nonwhite i.site
Iteration 0: log likelihood = -555.85446 Iteration 1: log likelihood = -534.67443 Iteration 2: log likelihood = -534.36284 Iteration 3: log likelihood = -534.36165 Iteration 4: log likelihood = -534.36165
Multinomial logistic regression Number of obs = 615 LR chi2(10) = 42.99 Prob > chi2 = 0.0000 Log likelihood = -534.36165 Pseudo R2 = 0.0387
------------------------------------------------------------------------------ insure | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Indemnity | (base outcome) -------------+---------------------------------------------------------------- Prepaid | age | -.011745 .0061946 -1.90 0.058 -.0238862 .0003962 male | .5616934 .2027465 2.77 0.006 .1643175 .9590693 nonwhite | .9747768 .2363213 4.12 0.000 .5115955 1.437958 | site | 2 | .1130359 .2101903 0.54 0.591 -.2989296 .5250013 3 | -.5879879 .2279351 -2.58 0.010 -1.034733 -.1412433 | _cons | .2697127 .3284422 0.82 0.412 -.3740222 .9134476 -------------+---------------------------------------------------------------- Uninsure | age | -.0077961 .0114418 -0.68 0.496 -.0302217 .0146294 male | .4518496 .3674867 1.23 0.219 -.268411 1.17211 nonwhite | .2170589 .4256361 0.51 0.610 -.6171725 1.05129 | site | 2 | -1.211563 .4705127 -2.57 0.010 -2.133751 -.2893747 3 | -.2078123 .3662926 -0.57 0.570 -.9257327 .510108 | _cons | -1.286943 .5923219 -2.17 0.030 -2.447872 -.1260134 ------------------------------------------------------------------------------
Output of Miscellaneous:MLogit --------------------------- Default value of Y = 1sample size mean st.dev. min max insure 615.00 1.5967 0.62208 1.0000 3.0000 age 615.00 44.468 14.174 18.111 86.073 male 615.00 0.25041 0.43325 0.00000 1.0000 nonwhite 615.00 0.19675 0.39754 0.00000 1.0000 isite2 615.00 0.37073 0.48300 0.00000 1.0000 isite3 615.00 0.31382 0.46404 0.00000 1.0000 Cons 615.00 1.0000 0.00000 1.0000 1.0000
sample size mean st.dev. min max Y indices 615.00 0.59675 0.62208 0.00000 2.0000 -675.64641529*
Report of Gradient Starting on Test
Obj= -675.646557531 Free Parameters index free Y=2:age 6 0.000000000000 Y=2:male 7 0.000000000000 Y=2:nonwhite 8 0.000000000000 Y=2:isite2 9 0.000000000000 Y=2:isite3 10 0.000000000000 Y=2:Cons 11 0.000000000000 Y=3:age 12 0.000000000000 Y=3:male 13 0.000000000000 Y=3:nonwhite 14 0.000000000000 Y=3:isite2 15 0.000000000000 Y=3:isite3 16 0.000000000000 Y=3:Cons 17 0.000000000000 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age 0.000000000000 Y=2:male 0.000000000000 Y=2:nonwhite 0.000000000000 Y=2:isite2 0.000000000000 Y=2:isite3 0.000000000000 Y=2:Cons 0.000000000000 Y=3:age 0.000000000000 Y=3:male 0.000000000000 Y=3:nonwhite 0.000000000000 Y=3:isite2 0.000000000000 Y=3:isite3 0.000000000000 Y=3:Cons 0.000000000000 -674.55505484* -672.80266631* -670.00295491* -665.56576072* -658.62639209* -648.01436402* -632.40049455* -565.17592819* -555.43249993* -555.37824425* -555.37823104* 1. f=-555.378 deltaX: 2.35698 deltaG: 588.098
Report of Gradient Iteration on Test
Obj= -555.378244250 Free Parameters index free Y=2:age 6-7.60231935463e-05 Y=2:male 7 -0.00187253985150 Y=2:nonwhite 8-3.05392001873e-05 Y=2:isite2 9-1.41592959729e-05 Y=2:isite3 10-1.66925131649e-05 Y=2:Cons 11-2.54740211765e-06 Y=3:age 12-1.44712465017e-05 Y=3:male 13 -0.00290140273033 Y=3:nonwhite 14 -0.00107782244121 Y=3:isite2 15 -0.00107912547628 Y=3:isite3 16 0.847612781393 Y=3:Cons 17 -2.19929868522 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -7.60231935463e-05 Y=2:male -0.00187253985150 Y=2:nonwhite -3.05392001873e-05 Y=2:isite2 -1.41592959729e-05 Y=2:isite3 -1.66925131649e-05 Y=2:Cons -2.54740211765e-06 Y=3:age -1.44712465017e-05 Y=3:male -0.00290140273033 Y=3:nonwhite -0.00107782244121 Y=3:isite2 -0.00107912547628 Y=3:isite3 0.847612781393 Y=3:Cons -2.19929868522 -535.52827716* -535.52825624* 2. f=-535.528 deltaX: 1.92099 deltaG: 54.9699
Report of Gradient Iteration on Test
Obj= -535.528277157 Free Parameters index free Y=2:age 6 -0.0100527628962 Y=2:male 7 0.532246731094 Y=2:nonwhite 8 0.887579141502 Y=2:isite2 9 0.0903589837479 Y=2:isite3 10 -0.564902436855 Y=2:Cons 11 0.217226866645 Y=3:age 12 0.00474554321745 Y=3:male 13 0.183185866679 Y=3:nonwhite 14 0.152895014321 Y=3:isite2 15 -1.20346180970 Y=3:isite3 16 0.0302907266284 Y=3:Cons 17 -1.93392071034 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0100527628962 Y=2:male 0.532246731094 Y=2:nonwhite 0.887579141502 Y=2:isite2 0.0903589837479 Y=2:isite3 -0.564902436855 Y=2:Cons 0.217226866645 Y=3:age 0.00474554321745 Y=3:male 0.183185866679 Y=3:nonwhite 0.152895014321 Y=3:isite2 -1.20346180970 Y=3:isite3 0.0302907266284 Y=3:Cons -1.93392071034 -534.58759809* -534.55024518* -534.55023884* 3. f=-534.55 deltaX: 0.686757 deltaG: 53.0643
Report of Gradient Iteration on Test
Obj= -534.550245181 Free Parameters index free Y=2:age 6 -0.0117193850291 Y=2:male 7 0.556381506602 Y=2:nonwhite 8 0.964747635917 Y=2:isite2 9 0.114420260032 Y=2:isite3 10 -0.580961478711 Y=2:Cons 11 0.268111835082 Y=3:age 12 -0.00835321843963 Y=3:male 13 0.364418929672 Y=3:nonwhite 14 0.347191111055 Y=3:isite2 15 -1.04652423147 Y=3:isite3 16 -0.130789545464 Y=3:Cons 17 -1.35054765039 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117193850291 Y=2:male 0.556381506602 Y=2:nonwhite 0.964747635917 Y=2:isite2 0.114420260032 Y=2:isite3 -0.580961478711 Y=2:Cons 0.268111835082 Y=3:age -0.00835321843963 Y=3:male 0.364418929672 Y=3:nonwhite 0.347191111055 Y=3:isite2 -1.04652423147 Y=3:isite3 -0.130789545464 Y=3:Cons -1.35054765039 -534.40701257* -534.40424989* -534.39683997* -534.39683756* 4. f=-534.397 deltaX: 0.195916 deltaG: 5.73388
Report of Gradient Iteration on Test
Obj= -534.396839974 Free Parameters index free Y=2:age 6 -0.0116267548883 Y=2:male 7 0.560758428396 Y=2:nonwhite 8 0.969463632119 Y=2:isite2 9 0.110547350397 Y=2:isite3 10 -0.589121880197 Y=2:Cons 11 0.266829639864 Y=3:age 12 -0.00547567110409 Y=3:male 13 0.405816263792 Y=3:nonwhite 14 0.223249074362 Y=3:isite2 15 -1.17279317293 Y=3:isite3 16 -0.175073316547 Y=3:Cons 17 -1.40773050528 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0116267548883 Y=2:male 0.560758428396 Y=2:nonwhite 0.969463632119 Y=2:isite2 0.110547350397 Y=2:isite3 -0.589121880197 Y=2:Cons 0.266829639864 Y=3:age -0.00547567110409 Y=3:male 0.405816263792 Y=3:nonwhite 0.223249074362 Y=3:isite2 -1.17279317293 Y=3:isite3 -0.175073316547 Y=3:Cons -1.40773050528 -534.36838112* -534.36833561* -534.36833482* 5. f=-534.368 deltaX: 0.111882 deltaG: 2.61384
Report of Gradient Iteration on Test
Obj= -534.368335611 Free Parameters index free Y=2:age 6 -0.0117605888148 Y=2:male 7 0.561216707653 Y=2:nonwhite 8 0.974656106078 Y=2:isite2 9 0.113637071064 Y=2:isite3 10 -0.587594103797 Y=2:Cons 11 0.269984185324 Y=3:age 12 -0.00768522745231 Y=3:male 13 0.437174321062 Y=3:nonwhite 14 0.245606054187 Y=3:isite2 15 -1.17557329357 Y=3:isite3 16 -0.197334831978 Y=3:Cons 17 -1.30537223647 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117605888148 Y=2:male 0.561216707653 Y=2:nonwhite 0.974656106078 Y=2:isite2 0.113637071064 Y=2:isite3 -0.587594103797 Y=2:Cons 0.269984185324 Y=3:age -0.00768522745231 Y=3:male 0.437174321062 Y=3:nonwhite 0.245606054187 Y=3:isite2 -1.17557329357 Y=3:isite3 -0.197334831978 Y=3:Cons -1.30537223647 -534.36314842* -534.36301867* -534.36301854* 6. f=-534.363 deltaX: 0.0412559 deltaG: 3.56314
Report of Gradient Iteration on Test
Obj= -534.363018670 Free Parameters index free Y=2:age 6 -0.0117290795474 Y=2:male 7 0.561692557753 Y=2:nonwhite 8 0.974416537032 Y=2:isite2 9 0.112624380757 Y=2:isite3 10 -0.588501941644 Y=2:Cons 11 0.269376024257 Y=3:age 12 -0.00727105321850 Y=3:male 13 0.444428852108 Y=3:nonwhite 14 0.218817924080 Y=3:isite2 15 -1.20467736013 Y=3:isite3 16 -0.203904159517 Y=3:Cons 17 -1.31161253856 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117290795474 Y=2:male 0.561692557753 Y=2:nonwhite 0.974416537032 Y=2:isite2 0.112624380757 Y=2:isite3 -0.588501941644 Y=2:Cons 0.269376024257 Y=3:age -0.00727105321850 Y=3:male 0.444428852108 Y=3:nonwhite 0.218817924080 Y=3:isite2 -1.20467736013 Y=3:isite3 -0.203904159517 Y=3:Cons -1.31161253856 -534.36199134* -534.36193806* -534.36193786* 7. f=-534.362 deltaX: 0.0234443 deltaG: 0.78376
Report of Gradient Iteration on Test
Obj= -534.361938056 Free Parameters index free Y=2:age 6 -0.0117528877771 Y=2:male 7 0.561619476487 Y=2:nonwhite 8 0.974986471555 Y=2:isite2 9 0.113241654351 Y=2:isite3 10 -0.587919731469 Y=2:Cons 11 0.269891019385 Y=3:age 12 -0.00779647867671 Y=3:male 13 0.449507727570 Y=3:nonwhite 14 0.223764677816 Y=3:isite2 15 -1.20395221105 Y=3:isite3 16 -0.206373111203 Y=3:Cons 17 -1.28945051708 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117528877771 Y=2:male 0.561619476487 Y=2:nonwhite 0.974986471555 Y=2:isite2 0.113241654351 Y=2:isite3 -0.587919731469 Y=2:Cons 0.269891019385 Y=3:age -0.00779647867671 Y=3:male 0.449507727570 Y=3:nonwhite 0.223764677816 Y=3:isite2 -1.20395221105 Y=3:isite3 -0.206373111203 Y=3:Cons -1.28945051708 -534.36172781* -534.36171804* -534.36170864* -534.36170860* 8. f=-534.362 deltaX: 0.00869961 deltaG: 0.865073
Report of Gradient Iteration on Test
Obj= -534.361708638 Free Parameters index free Y=2:age 6 -0.0117431978357 Y=2:male 7 0.561695733395 Y=2:nonwhite 8 0.974767307364 Y=2:isite2 9 0.112976017635 Y=2:isite3 10 -0.588096396680 Y=2:Cons 11 0.269683580399 Y=3:age 12 -0.00769128442119 Y=3:male 13 0.450344033052 Y=3:nonwhite 14 0.217901844784 Y=3:isite2 15 -1.20975680526 Y=3:isite3 16 -0.207101700658 Y=3:Cons 17 -1.29193586279 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117431978357 Y=2:male 0.561695733395 Y=2:nonwhite 0.974767307364 Y=2:isite2 0.112976017635 Y=2:isite3 -0.588096396680 Y=2:Cons 0.269683580399 Y=3:age -0.00769128442119 Y=3:male 0.450344033052 Y=3:nonwhite 0.217901844784 Y=3:isite2 -1.20975680526 Y=3:isite3 -0.207101700658 Y=3:Cons -1.29193586279 -534.36166118* -534.36166114* 9. f=-534.362 deltaX: 0.00511699 deltaG: 0.183982
Report of Gradient Iteration on Test
Obj= -534.361661178 Free Parameters index free Y=2:age 6 -0.0117471893937 Y=2:male 7 0.561678373997 Y=2:nonwhite 8 0.974839112563 Y=2:isite2 9 0.113090461324 Y=2:isite3 10 -0.587965524629 Y=2:Cons 11 0.269763186593 Y=3:age 12 -0.00780587654440 Y=3:male 13 0.451494725396 Y=3:nonwhite 14 0.218510212682 Y=3:isite2 15 -1.21002712006 Y=3:isite3 16 -0.207595991030 Y=3:Cons 17 -1.28702497003 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117471893937 Y=2:male 0.561678373997 Y=2:nonwhite 0.974839112563 Y=2:isite2 0.113090461324 Y=2:isite3 -0.587965524629 Y=2:Cons 0.269763186593 Y=3:age -0.00780587654440 Y=3:male 0.451494725396 Y=3:nonwhite 0.218510212682 Y=3:isite2 -1.21002712006 Y=3:isite3 -0.207595991030 Y=3:Cons -1.28702497003 -534.36165317* -534.36165099* -534.36165097* 10. f=-534.362 deltaX: 0.00169821 deltaG: 0.155233
Report of Gradient Iteration on Test
Obj= -534.361650986 Free Parameters index free Y=2:age 6 -0.0117450577617 Y=2:male 7 0.561692232033 Y=2:nonwhite 8 0.974787277172 Y=2:isite2 9 0.113034053843 Y=2:isite3 10 -0.588003487634 Y=2:Cons 11 0.269716757628 Y=3:age 12 -0.00778025829240 Y=3:male 13 0.451563306636 Y=3:nonwhite 14 0.217397310125 Y=3:isite2 15 -1.21106296906 Y=3:isite3 16 -0.207677520025 Y=3:Cons 17 -1.28776706637 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117450577617 Y=2:male 0.561692232033 Y=2:nonwhite 0.974787277172 Y=2:isite2 0.113034053843 Y=2:isite3 -0.588003487634 Y=2:Cons 0.269716757628 Y=3:age -0.00778025829240 Y=3:male 0.451563306636 Y=3:nonwhite 0.217397310125 Y=3:isite2 -1.21106296906 Y=3:isite3 -0.207677520025 Y=3:Cons -1.28776706637 -534.36164909* -534.36164895* -534.36164891* -534.36164891* 11. f=-534.362 deltaX: 0.00102409 deltaG: 0.0213223
Report of Gradient Iteration on Test
Obj= -534.361648911 Free Parameters index free Y=2:age 6 -0.0117452380421 Y=2:male 7 0.561691891827 Y=2:nonwhite 8 0.974783431311 Y=2:isite2 9 0.113042206228 Y=2:isite3 10 -0.587984273841 Y=2:Cons 11 0.269718300678 Y=3:age 12 -0.00779854149515 Y=3:male 13 0.451834716074 Y=3:nonwhite 14 0.217193906513 Y=3:isite2 15 -1.21143275434 Y=3:isite3 16 -0.207800710727 Y=3:Cons 17 -1.28688331744 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117452380421 Y=2:male 0.561691891827 Y=2:nonwhite 0.974783431311 Y=2:isite2 0.113042206228 Y=2:isite3 -0.587984273841 Y=2:Cons 0.269718300678 Y=3:age -0.00779854149515 Y=3:male 0.451834716074 Y=3:nonwhite 0.217193906513 Y=3:isite2 -1.21143275434 Y=3:isite3 -0.207800710727 Y=3:Cons -1.28688331744 -534.36164885* -534.36164881* -534.36164881* 12. f=-534.362 deltaX: 0.000194352 deltaG: 0.0109102
Report of Gradient Iteration on Test
Obj= -534.361648806 Free Parameters index free Y=2:age 6 -0.0117449874937 Y=2:male 7 0.561693427025 Y=2:nonwhite 8 0.974777472372 Y=2:isite2 9 0.113035541801 Y=2:isite3 10 -0.587989156621 Y=2:Cons 11 0.269712886412 Y=3:age 12 -0.00779500082257 Y=3:male 13 0.451831762096 Y=3:nonwhite 14 0.217076594980 Y=3:isite2 15 -1.21153471366 Y=3:isite3 16 -0.207804488345 Y=3:Cons 17 -1.28699926582 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117449874937 Y=2:male 0.561693427025 Y=2:nonwhite 0.974777472372 Y=2:isite2 0.113035541801 Y=2:isite3 -0.587989156621 Y=2:Cons 0.269712886412 Y=3:age -0.00779500082257 Y=3:male 0.451831762096 Y=3:nonwhite 0.217076594980 Y=3:isite2 -1.21153471366 Y=3:isite3 -0.207804488345 Y=3:Cons -1.28699926582 -534.36164880* -534.36164880* -534.36164880* 13. f=-534.362 deltaX: 6.45179e-05 deltaG: 0.00201316
Report of Gradient Iteration on Test
Obj= -534.361648799 Free Parameters index free Y=2:age 6 -0.0117450118861 Y=2:male 7 0.561693269874 Y=2:nonwhite 8 0.974777417800 Y=2:isite2 9 0.113036468871 Y=2:isite3 10 -0.587987596286 Y=2:Cons 11 0.269713233455 Y=3:age 12 -0.00779634127403 Y=3:male 13 0.451847490164 Y=3:nonwhite 14 0.217072877670 Y=3:isite2 15 -1.21154887247 Y=3:isite3 16 -0.207810784080 Y=3:Cons 17 -1.28693880081 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117450118861 Y=2:male 0.561693269874 Y=2:nonwhite 0.974777417800 Y=2:isite2 0.113036468871 Y=2:isite3 -0.587987596286 Y=2:Cons 0.269713233455 Y=3:age -0.00779634127403 Y=3:male 0.451847490164 Y=3:nonwhite 0.217072877670 Y=3:isite2 -1.21154887247 Y=3:isite3 -0.207810784080 Y=3:Cons -1.28693880081 -534.36164880* -534.36164880* -534.36164880* 14. f=-534.362 deltaX: 1.89573e-05 deltaG: 0.00120423
Report of Gradient Iteration on Test
Obj= -534.361648798 Free Parameters index free Y=2:age 6 -0.0117449878302 Y=2:male 7 0.561693423847 Y=2:nonwhite 8 0.974776852797 Y=2:isite2 9 0.113035824220 Y=2:isite3 10 -0.587988065731 Y=2:Cons 11 0.269712715391 Y=3:age 12 -0.00779600875833 Y=3:male 13 0.451847496268 Y=3:nonwhite 14 0.217061164596 Y=3:isite2 15 -1.21155927093 Y=3:isite3 16 -0.207811335736 Y=3:Cons 17 -1.28694940236 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117449878302 Y=2:male 0.561693423847 Y=2:nonwhite 0.974776852797 Y=2:isite2 0.113035824220 Y=2:isite3 -0.587988065731 Y=2:Cons 0.269712715391 Y=3:age -0.00779600875833 Y=3:male 0.451847496268 Y=3:nonwhite 0.217061164596 Y=3:isite2 -1.21155927093 Y=3:isite3 -0.207811335736 Y=3:Cons -1.28694940236 -534.36164880* -534.36164880* -534.36164880* 15. f=-534.362 deltaX: 7.28111e-06 deltaG: 0.000196494
Report of Gradient Iteration on Test
Obj= -534.361648798 Free Parameters index free Y=2:age 6 -0.0117449903843 Y=2:male 7 0.561693413358 Y=2:nonwhite 8 0.974776855670 Y=2:isite2 9 0.113035916282 Y=2:isite3 10 -0.587987906301 Y=2:Cons 11 0.269712753776 Y=3:age 12 -0.00779615284980 Y=3:male 13 0.451849359063 Y=3:nonwhite 14 0.217060410875 Y=3:isite2 15 -1.21156123681 Y=3:isite3 16 -0.207812146853 Y=3:Cons 17 -1.28694273920 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117449903843 Y=2:male 0.561693413358 Y=2:nonwhite 0.974776855670 Y=2:isite2 0.113035916282 Y=2:isite3 -0.587987906301 Y=2:Cons 0.269712753776 Y=3:age -0.00779615284980 Y=3:male 0.451849359063 Y=3:nonwhite 0.217060410875 Y=3:isite2 -1.21156123681 Y=3:isite3 -0.207812146853 Y=3:Cons -1.28694273920 -534.36164880* -534.36164880*
Finished: 3:WEAK Y=2:age Y=2:male Y=2:nonwhite Y=2:isite2 Y=2:isite3 Y=2:Cons Y=3:age Y=3:male Y=3:nonwhite Y=3:isite2 Y=3:isite3 Y=3:Cons Free Vector -0.011745 0.56169 0.97478 0.11304 -0.58799 0.26971 -0.0077961 0.45185 0.21706 -1.2116 -0.20781 -1.2869 Gradient 6.4692e-05 -9.5020e-07 1.0507e-06 8.4777e-07 6.7238e-07 3.5805e-07 -0.00012708 1.8985e-06 -2.0062e-06 -1.7034e-06 -5.9662e-07 -4.1028e-07 Std.Error 0.0062657 0.20220 0.23500 0.20922 0.22547 0.33087 0.013290 0.38553 0.45364 0.48973 0.37880 0.63520
Take care interpreting SE for Quasi-Newton algorithms
Report of Iteration Done on Test
Obj= -534.361648798 Free Parameters index free stderr Y=2:age 6 -0.0117449879934 0.00626570540815 Y=2:male 7 0.561693428283 0.202195935676 Y=2:nonwhite 8 0.974776797699 0.235001739587 Y=2:isite2 9 0.113035852985 0.209222737479 Y=2:isite3 10 -0.587987950387 0.225471433292 Y=2:Cons 11 0.269712701856 0.330866619656 Y=3:age 12 -0.00779612195905 0.0132904774735 Y=3:male 13 0.451849385777 0.385526879953 Y=3:nonwhite 14 0.217059227487 0.453638241712 Y=3:isite2 15 -1.21156230532 0.489732709747 Y=3:isite3 16 -0.207812210676 0.378797153781 Y=3:Cons 17 -1.28694369346 0.635198399656 Actual Parameters Value Y=10 0.000000000000 Y=11 0.000000000000 Y=12 0.000000000000 Y=13 0.000000000000 Y=14 0.000000000000 Y=15 0.000000000000 Y=2:age -0.0117449879934 Y=2:male 0.561693428283 Y=2:nonwhite 0.974776797699 Y=2:isite2 0.113035852985 Y=2:isite3 -0.587987950387 Y=2:Cons 0.269712701856 Y=3:age -0.00779612195905 Y=3:male 0.451849385777 Y=3:nonwhite 0.217059227487 Y=3:isite2 -1.21156230532 Y=3:isite3 -0.207812210676 Y=3:Cons -1.28694369346 Y = 2 Estimate Std.Err t-ratio age -0.011745 0.0062657 -1.8745 male 0.56169 0.20220 2.7780 nonwhite 0.97478 0.23500 4.1480 isite2 0.11304 0.20922 0.54027 isite3 -0.58799 0.22547 -2.6078 Cons 0.26971 0.33087 0.81517 Y = 3 Estimate Std.Err t-ratio age -0.0077961 0.013290 -0.58659 male 0.45185 0.38553 1.1720 nonwhite 0.21706 0.45364 0.47849 isite2 -1.2116 0.48973 -2.4739 isite3 -0.20781 0.37880 -0.54861 Cons -1.2869 0.63520 -2.0260 ... finished.
Global functions| Functions | ||
 RunMLogitTest |
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Global 
RunMLogitTest