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 15:54:51.420250
If you drag this HTML file into the Calc application of OpenOffice, or the spreadsheet of LibreOffice, you will be able to perform additional calculations.
| Report file: | 07estimationMonteCarlo_mlhs_anti.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6879.527 |
| Final log likelihood: | -5214.762 |
| Likelihood ratio test for the init. model: | 3329.53 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10439.52 |
| Bayesian Information Criterion: | 10473.62 |
| Final gradient norm: | 1.5179E-02 |
| Number of draws: | 2000 |
| Draws generation time: | 0:00:20.609899 |
| Types of draws: | ['B_TIME_RND: NORMAL_MLHS_ANTI'] |
| Nbr of threads: | 36 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Relative projected gradient: | 2.583307e-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 = 2.6e-06 <= 6.1e-06 |
| Optimization time: | 0:01:25.112830 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.136 | 0.0516 | 2.64 | 0.0082 | 0.0517 | 2.64 | 0.00836 |
| ASC_TRAIN | -0.402 | 0.0634 | -6.33 | 2.41e-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 | 1.65 | 0.139 | 11.9 | 0 | 0.133 | 12.4 | 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 | 0.00223 | 0.654 | -10.6 | 0 |
| B_COST | ASC_CAR | 0.000184 | 0.0566 | -18 | 0 | 0.000134 | 0.03 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000135 | -0.0337 | -9.72 | 0 | -0.000295 | -0.0519 | -7.95 | 2e-15 |
| B_TIME | ASC_CAR | -0.00393 | -0.641 | -15.2 | 0 | -0.00386 | -0.637 | -15.4 | 0 |
| B_TIME | ASC_TRAIN | -0.00454 | -0.602 | -11.2 | 0 | -0.00468 | -0.607 | -11.2 | 0 |
| B_TIME | B_COST | 0.00238 | 0.318 | -8.41 | 0 | 0.00371 | 0.367 | -8.29 | 2.22e-16 |
| B_TIME_S | ASC_CAR | 0.00297 | 0.414 | 12 | 0 | 0.00285 | 0.414 | 12.5 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00179 | 0.203 | 14.6 | 0 | 0.00141 | 0.161 | 14.8 | 0 |
| B_TIME_S | B_COST | -0.00259 | -0.296 | 17.4 | 0 | -0.00322 | -0.28 | 16.5 | 0 |
| B_TIME_S | B_TIME | -0.0128 | -0.772 | 16.1 | 0 | -0.0115 | -0.739 | 16.8 | 0 |
Smallest eigenvalue: 31.5198
Largest eigenvalue: 1001.82
Condition number: 31.7839