biogeme 3.2.8 [2021-07-26]
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 2021-07-26 18:03:43.437019
| Report file: | 01logitBis.html |
| Database name: | swissmetro |
Example of a logit model with three alternatives: Train, Car and Swissmetro. Same as 01logit, using bioLinearUtility, and introducing some options and features.
| Number of estimated parameters: | 4 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Null log likelihood: | -6964.663 |
| Init log likelihood: | -5533.155 |
| Final log likelihood: | -5331.252 |
| Likelihood ratio test for the null model: | 3266.822 |
| Rho-square for the null model: | 0.235 |
| Rho-square-bar for the null model: | 0.234 |
| Likelihood ratio test for the init. model: | 403.8058 |
| Rho-square for the init. model: | 0.0365 |
| Rho-square-bar for the init. model: | 0.0358 |
| Akaike Information Criterion: | 10670.5 |
| Bayesian Information Criterion: | 10697.78 |
| Final gradient norm: | 4.5802E-03 |
| Bootstrapping time: | 0:00:11.292297 |
| Nbr of threads: | 2 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Proportion analytical hessian: | 100.0% |
| Relative projected gradient: | 5.423705e-07 |
| Relative change: | 0.0030568198881113506 |
| Number of iterations: | 3 |
| Number of function evaluations: | 10 |
| Number of gradient evaluations: | 4 |
| Number of hessian evaluations: | 4 |
| Cause of termination: | Relative gradient = 5.4e-07 <= 6.1e-06 |
| Optimization time: | 0:00:00.115150 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value | Bootstrap[100] Std err | Bootstrap t-test | Bootstrap p-value |
|---|---|---|---|---|---|---|---|---|---|---|
| ASC_CAR | -0.155 | 0.0432 | -3.58 | 0.000348 | 0.0582 | -2.66 | 0.00785 | 0.0599 | -2.58 | 0.00785 |
| ASC_TRAIN | -0.701 | 0.0549 | -12.8 | 0 | 0.0826 | -8.49 | 0 | 0.0846 | -8.29 | 0 |
| B_COST | -1.08 | 0.0518 | -20.9 | 0 | 0.0682 | -15.9 | 0 | 0.0713 | -15.2 | 0 |
| B_TIME | -1.28 | 0.0569 | -22.5 | 0 | 0.104 | -12.3 | 0 | 0.107 | -11.9 | 0 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value | Boot. cov. | Boot. corr. | Boot. t-test | Boot. p-value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | ASC_CAR | 0.00138 | 0.58 | -11.9 | 0 | 0.0039 | 0.812 | -11.2 | 0 | 0.00422 | 0.832 | -11.4 | 0 |
| B_COST | ASC_CAR | 0.000485 | 0.216 | -15.5 | 0 | 2.86e-05 | 0.00722 | -10.4 | 0 | 0.0004 | 0.0935 | -10.5 | 0 |
| B_COST | ASC_TRAIN | 8.22e-06 | 0.00289 | -5.08 | 3.85e-07 | -0.000831 | -0.147 | -3.34 | 0.000842 | -0.000656 | -0.109 | -3.29 | 0.00101 |
| B_TIME | ASC_CAR | -0.00144 | -0.585 | -12.6 | 0 | -0.00482 | -0.796 | -7.27 | 3.72e-13 | -0.00495 | -0.771 | -7.11 | 1.15e-12 |
| B_TIME | ASC_TRAIN | -0.00225 | -0.722 | -5.56 | 2.69e-08 | -0.0076 | -0.883 | -3.18 | 0.00147 | -0.00803 | -0.886 | -3.1 | 0.00195 |
| B_TIME | B_COST | 0.00055 | 0.187 | -2.79 | 0.0052 | 0.0022 | 0.309 | -1.84 | 0.0658 | 0.00234 | 0.306 | -1.78 | 0.0749 |
Smallest eigenvalue: 159.083
Largest eigenvalue: 1469.54
Condition number: 9.23759