biogeme 3.2.6 [2020-05-05]
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 2020-05-05 15:53:20.797996
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| Report file: | 07estimationMonteCarlo_anti_500.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6879.478 |
| Final log likelihood: | -5215.486 |
| Likelihood ratio test for the init. model: | 3327.985 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10440.97 |
| Bayesian Information Criterion: | 10475.07 |
| Final gradient norm: | 1.7418E-02 |
| Number of draws: | 500 |
| Draws generation time: | 0:00:04.147471 |
| Types of draws: | ['B_TIME_RND: NORMAL_ANTI'] |
| Nbr of threads: | 36 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Relative projected gradient: | 2.941421e-06 |
| Number of iterations: | 8 |
| Number of function evaluations: | 25 |
| Number of gradient evaluations: | 9 |
| Number of hessian evaluations: | 9 |
| Cause of termination: | Relative gradient = 2.9e-06 <= 6.1e-06 |
| Optimization time: | 0:00:21.168885 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.135 | 0.0516 | 2.62 | 0.00867 | 0.0517 | 2.62 | 0.00891 |
| ASC_TRAIN | -0.401 | 0.0635 | -6.31 | 2.84e-10 | 0.0662 | -6.05 | 1.44e-09 |
| B_COST | -1.28 | 0.0629 | -20.4 | 0 | 0.0859 | -14.9 | 0 |
| B_TIME | -2.25 | 0.119 | -19 | 0 | 0.117 | -19.3 | 0 |
| B_TIME_S | 1.64 | 0.14 | 11.7 | 0 | 0.135 | 12.1 | 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 | -10.5 | 0 | 0.00224 | 0.654 | -10.5 | 0 |
| B_COST | ASC_CAR | 0.000185 | 0.057 | -17.9 | 0 | 0.000135 | 0.0304 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000133 | -0.0332 | -9.7 | 0 | -0.00029 | -0.051 | -7.93 | 2.22e-15 |
| B_TIME | ASC_CAR | -0.00392 | -0.641 | -15.2 | 0 | -0.00386 | -0.638 | -15.4 | 0 |
| B_TIME | ASC_TRAIN | -0.00454 | -0.602 | -11.2 | 0 | -0.00468 | -0.605 | -11.2 | 0 |
| B_TIME | B_COST | 0.00237 | 0.317 | -8.4 | 0 | 0.00368 | 0.366 | -8.28 | 2.22e-16 |
| B_TIME_S | ASC_CAR | 0.00295 | 0.409 | 11.8 | 0 | 0.0028 | 0.401 | 12.2 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00172 | 0.194 | 14.4 | 0 | 0.00124 | 0.139 | 14.4 | 0 |
| B_TIME_S | B_COST | -0.0026 | -0.296 | 17.2 | 0 | -0.0032 | -0.276 | 16.3 | 0 |
| B_TIME_S | B_TIME | -0.0127 | -0.767 | 16 | 0 | -0.0115 | -0.727 | 16.6 | 0 |
Smallest eigenvalue: 31.4786
Largest eigenvalue: 1003
Condition number: 31.863