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 15:54:22.864534
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.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6878.709 |
| Final log likelihood: | -5214.338 |
| Likelihood ratio test for the init. model: | 3328.742 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10438.68 |
| Bayesian Information Criterion: | 10472.78 |
| Final gradient norm: | 2.9007E-02 |
| Number of draws: | 2000 |
| Draws generation time: | 0:00:19.490351 |
| Types of draws: | ['B_TIME_RND: NORMAL'] |
| Nbr of threads: | 36 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Relative projected gradient: | 3.985499e-06 |
| Number of iterations: | 6 |
| Number of function evaluations: | 19 |
| Number of gradient evaluations: | 7 |
| Number of hessian evaluations: | 7 |
| Cause of termination: | Relative gradient = 4e-06 <= 6.1e-06 |
| Optimization time: | 0:01:02.885711 |
| 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 | 0.00812 | 0.0517 | 2.64 | 0.00827 |
| ASC_TRAIN | -0.402 | 0.0635 | -6.33 | 2.38e-10 | 0.0659 | -6.1 | 1.06e-09 |
| B_COST | -1.29 | 0.0631 | -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 | 0.132 | 12.5 | 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 | 0.000183 | 0.0563 | -18 | 0 | 0.000129 | 0.029 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000134 | -0.0335 | -9.71 | 0 | -0.000293 | -0.0515 | -7.94 | 2e-15 |
| B_TIME | ASC_CAR | -0.00393 | -0.641 | -15.3 | 0 | -0.00385 | -0.637 | -15.4 | 0 |
| B_TIME | ASC_TRAIN | -0.00454 | -0.603 | -11.2 | 0 | -0.00468 | -0.607 | -11.2 | 0 |
| B_TIME | B_COST | 0.00239 | 0.318 | -8.42 | 0 | 0.00372 | 0.368 | -8.3 | 0 |
| B_TIME_S | ASC_CAR | 0.00295 | 0.413 | 12 | 0 | 0.00282 | 0.412 | 12.6 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00178 | 0.202 | 14.7 | 0 | 0.00139 | 0.159 | 14.9 | 0 |
| B_TIME_S | B_COST | -0.0026 | -0.298 | 17.4 | 0 | -0.00323 | -0.283 | 16.6 | 0 |
| B_TIME_S | B_TIME | -0.0127 | -0.771 | 16.1 | 0 | -0.0114 | -0.737 | 16.8 | 0 |
Smallest eigenvalue: 31.6187
Largest eigenvalue: 1001.09
Condition number: 31.6613