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 19:38:22.056119
| Report file: | 05normalMixture.html |
| Database name: | swissmetro |
Example of a mixture of logit models with three alternatives, approximated using Monte-Carlo integration.
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6879.466 |
| Final log likelihood: | -5214.763 |
| Likelihood ratio test for the init. model: | 3329.406 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10439.53 |
| Bayesian Information Criterion: | 10473.63 |
| Final gradient norm: | 3.2284E-02 |
| Number of draws: | 100000 |
| Draws generation time: | 0:15:28.402315 |
| Types of draws: | ['B_TIME_RND: NORMAL'] |
| Nbr of threads: | 36 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Proportion analytical hessian: | 100.0% |
| Relative projected gradient: | 5.617179e-06 |
| Relative change: | 0.00013096016946101408 |
| Number of iterations: | 7 |
| Number of function evaluations: | 22 |
| Number of gradient evaluations: | 8 |
| Number of hessian evaluations: | 8 |
| Cause of termination: | Relative gradient = 5.6e-06 <= 6.1e-06 |
| Optimization time: | 1:12:09.259786 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.137 | 0.0516 | 2.66 | 0.00784 | 0.0517 | 2.65 | 0.00797 |
| ASC_TRAIN | -0.402 | 0.0635 | -6.33 | 2.47e-10 | 0.0659 | -6.1 | 1.07e-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 | 1.66 | 0.138 | 12 | 0 | 0.132 | 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 | 0.000183 | 0.0561 | -18 | 0 | 0.000127 | 0.0285 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000137 | -0.0343 | -9.72 | 0 | -0.000304 | -0.0534 | -7.94 | 2e-15 |
| B_TIME | ASC_CAR | -0.00394 | -0.641 | -15.2 | 0 | -0.00386 | -0.637 | -15.4 | 0 |
| B_TIME | ASC_TRAIN | -0.00456 | -0.603 | -11.2 | 0 | -0.0047 | -0.609 | -11.2 | 0 |
| B_TIME | B_COST | 0.00238 | 0.317 | -8.43 | 0 | 0.00373 | 0.369 | -8.33 | 0 |
| B_TIME_S | ASC_CAR | 0.00298 | 0.416 | 12.1 | 0 | 0.00284 | 0.416 | 12.7 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00181 | 0.206 | 14.7 | 0 | 0.00145 | 0.167 | 15 | 0 |
| B_TIME_S | B_COST | -0.00259 | -0.296 | 17.5 | 0 | -0.00322 | -0.283 | 16.6 | 0 |
| B_TIME_S | B_TIME | -0.0127 | -0.773 | 16.2 | 0 | -0.0114 | -0.741 | 16.9 | 0 |
Smallest eigenvalue: 31.5454
Largest eigenvalue: 1001.03
Condition number: 31.7329