biogeme 3.2.6 [2020-06-02]
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 2020-06-02 10:58:19.613552
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: | 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 |
| Init log likelihood: | -6964.663 |
| Final log likelihood: | -5331.252 |
| Likelihood ratio test for the init. model: | 3266.822 |
| Rho-square for the init. model: | 0.235 |
| Rho-square-bar for the init. model: | 0.234 |
| Akaike Information Criterion: | 10670.5 |
| Bayesian Information Criterion: | 10697.78 |
| Final gradient norm: | 3.3915E-02 |
| Bootstrapping time: | 0:00:32.699642 |
| Nbr of threads: | 2 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Proportion analytical hessian: | 100.0% |
| Relative projected gradient: | 4.686846e-06 |
| Number of iterations: | 9 |
| Number of function evaluations: | 18 |
| Number of gradient evaluations: | 4 |
| Number of hessian evaluations: | 4 |
| Cause of termination: | Relative gradient = 4.7e-06 <= 6.1e-06 |
| Stochastic Newton iterations: | 3 |
| Optimization time: | 0:00:00.303341 |
| 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 | 0.000347 | 0.0582 | -2.66 | 0.00783 | 0.0305 | -5.07 | 0.00783 |
| ASC_TRAIN | -0.701 | 0.0549 | -12.8 | 0 | 0.0826 | -8.49 | 0 | 0.0365 | -19.2 | 0 |
| B_COST | -1.08 | 0.0518 | -20.9 | 0 | 0.0682 | -15.9 | 0 | 0.037 | -29.3 | 0 |
| B_TIME | -1.28 | 0.0569 | -22.5 | 0 | 0.104 | -12.3 | 0 | 0.0648 | -19.7 | 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 | 0.000388 | 0.349 | -14.2 | 0 |
| B_COST | ASC_CAR | 0.000485 | 0.216 | -15.5 | 0 | 2.87e-05 | 0.00723 | -10.4 | 0 | 0.000126 | 0.111 | -20.5 | 0 |
| B_COST | ASC_TRAIN | 8.22e-06 | 0.00289 | -5.08 | 3.87e-07 | -0.000831 | -0.147 | -3.34 | 0.000843 | 0.000572 | 0.424 | -9.69 | 0 |
| B_TIME | ASC_CAR | -0.00144 | -0.585 | -12.6 | 0 | -0.00482 | -0.796 | -7.26 | 3.73e-13 | -0.00148 | -0.747 | -12.5 | 0 |
| B_TIME | ASC_TRAIN | -0.00225 | -0.722 | -5.56 | 2.71e-08 | -0.0076 | -0.883 | -3.18 | 0.00148 | -0.00202 | -0.855 | -5.89 | 3.83e-09 |
| B_TIME | B_COST | 0.00055 | 0.187 | -2.79 | 0.00521 | 0.0022 | 0.309 | -1.84 | 0.0659 | -0.00123 | -0.513 | -2.17 | 0.0303 |
Smallest eigenvalue: 159.084
Largest eigenvalue: 1469.55
Condition number: 9.23759