biogeme 3.2.6 [2020-06-03]
Python package
Home page: http://biogeme.epfl.ch
Submit questions to https://groups.google.com/d/forum/biogeme
Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)
This file has automatically been generated on 2020-06-03 13:19:27.959653
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| Report file: | 05normalMixture_allAlgos_Simple bounds hybrid iCG.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6879.717 |
| Final log likelihood: | -5214.841 |
| Likelihood ratio test for the init. model: | 3329.752 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10439.68 |
| Bayesian Information Criterion: | 10473.78 |
| Final gradient norm: | 1.3139E-03 |
| Number of draws: | 100000 |
| Draws generation time: | 0:15:44.891828 |
| Types of draws: | ['B_TIME_RND: NORMAL'] |
| Nbr of threads: | 36 |
| Algorithm: | Hybrid Newton [50.0%] with trust region for simple bound constraints |
| Proportion analytical hessian: | 50.0% |
| Relative projected gradient: | 2.764667e-07 |
| Number of iterations: | 9 |
| Number of function evaluations: | 28 |
| Number of gradient evaluations: | 10 |
| Number of hessian evaluations: | 5 |
| Cause of termination: | Relative gradient = 2.8e-07 <= 6.1e-06 |
| Optimization time: | 0:50:04.781812 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.137 | 0.0516 | 2.65 | 0.00795 | 0.0517 | 2.65 | 0.00806 |
| ASC_TRAIN | -0.402 | 0.0634 | -6.33 | 2.45e-10 | 0.0658 | -6.1 | 1.05e-09 |
| B_COST | -1.29 | 0.063 | -20.4 | 0 | 0.0863 | -14.9 | 0 |
| B_TIME | -2.26 | 0.119 | -19 | 0 | 0.117 | -19.3 | 0 |
| B_TIME_S | -1.66 | 0.138 | -12 | 0 | 0.131 | -12.6 | 0 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | ASC_CAR | 0.00204 | 0.623 | -10.6 | 0 | 0.00223 | 0.655 | -10.7 | 0 |
| B_COST | ASC_CAR | 0.000186 | 0.0571 | -18 | 0 | 0.000133 | 0.0297 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000136 | -0.034 | -9.72 | 0 | -0.000302 | -0.0531 | -7.94 | 2e-15 |
| B_TIME | ASC_CAR | -0.00394 | -0.641 | -15.3 | 0 | -0.00385 | -0.637 | -15.4 | 0 |
| B_TIME | ASC_TRAIN | -0.00456 | -0.604 | -11.2 | 0 | -0.00469 | -0.61 | -11.2 | 0 |
| B_TIME | B_COST | 0.00237 | 0.316 | -8.42 | 0 | 0.00372 | 0.368 | -8.32 | 0 |
| B_TIME_S | ASC_CAR | -0.00297 | -0.416 | -10.8 | 0 | -0.00282 | -0.416 | -11.2 | 0 |
| B_TIME_S | ASC_TRAIN | -0.00182 | -0.207 | -7.67 | 1.69e-14 | -0.00145 | -0.168 | -8.02 | 1.11e-15 |
| B_TIME_S | B_COST | 0.00257 | 0.295 | -2.77 | 0.00558 | 0.0032 | 0.282 | -2.74 | 0.00611 |
| B_TIME_S | B_TIME | 0.0127 | 0.773 | 6.82 | 9.14e-12 | 0.0114 | 0.74 | 6.66 | 2.65e-11 |
Smallest eigenvalue: 31.6664
Largest eigenvalue: 1001.57
Condition number: 31.6288