RunMLogitTest.ox
Replicate mlogit example in Stata using the MLogit objective.
decl ml = new MLogit("Test","mlogit_example.dta","insure",
"age male nonwhite isite2 isite3");
ml->Estimate();
Stata Output
. 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
------------------------------------------------------------------------------
My Output (may be out of date)
Output of Miscellaneous:MLogit
---------------------------
Default value of Y = 1
sample 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
Global
RunMLogitTest
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