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 13:19:43.711431
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: | 06unifMixture.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6921.984 |
| Final log likelihood: | -5214.879 |
| Likelihood ratio test for the init. model: | 3414.211 |
| Rho-square for the init. model: | 0.247 |
| Rho-square-bar for the init. model: | 0.246 |
| Akaike Information Criterion: | 10439.76 |
| Bayesian Information Criterion: | 10473.86 |
| Final gradient norm: | 2.0309E-02 |
| Number of draws: | 100000 |
| Draws generation time: | 0:12:50.907421 |
| Types of draws: | ['B_TIME_RND: UNIFORMSYM'] |
| Nbr of threads: | 36 |
| Algorithm: | BFGS with trust region for simple bound constraints |
| Proportion analytical hessian: | 0.0% |
| Relative projected gradient: | 3.898708e-06 |
| Number of iterations: | 30 |
| Number of function evaluations: | 91 |
| Number of gradient evaluations: | 31 |
| Number of hessian evaluations: | 0 |
| Cause of termination: | Relative gradient = 3.9e-06 <= 6.1e-06 |
| Optimization time: | 2:23:43.333429 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.145 | 0.0527 | 2.76 | 0.00584 | 0.0533 | 2.72 | 0.00646 |
| ASC_TRAIN | -0.385 | 0.0639 | -6.03 | 1.68e-09 | 0.066 | -5.83 | 5.6e-09 |
| B_COST | -1.28 | 0.0628 | -20.4 | 0 | 0.0866 | -14.8 | 0 |
| B_TIME | -2.32 | 0.129 | -18 | 0 | 0.126 | -18.4 | 0 |
| B_TIME_S | 2.88 | 0.215 | 13.4 | 0 | 0.2 | 14.4 | 0 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | ASC_CAR | 0.00218 | 0.65 | -10.6 | 0 | 0.00241 | 0.685 | -10.9 | 0 |
| B_COST | ASC_CAR | 0.000185 | 0.0559 | -17.9 | 0 | 0.000172 | 0.0373 | -14.2 | 0 |
| B_COST | ASC_TRAIN | -0.000182 | -0.0455 | -9.76 | 0 | -0.00032 | -0.0559 | -7.99 | 1.33e-15 |
| B_TIME | ASC_CAR | -0.00446 | -0.657 | -14.7 | 0 | -0.00446 | -0.663 | -14.8 | 0 |
| B_TIME | ASC_TRAIN | -0.00531 | -0.645 | -10.9 | 0 | -0.0055 | -0.66 | -11 | 0 |
| B_TIME | B_COST | 0.00234 | 0.29 | -8.29 | 2.22e-16 | 0.00353 | 0.323 | -8.16 | 4.44e-16 |
| B_TIME_S | ASC_CAR | 0.00554 | 0.491 | 14.1 | 0 | 0.00551 | 0.517 | 15.3 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00475 | 0.347 | 16.2 | 0 | 0.00455 | 0.345 | 17.4 | 0 |
| B_TIME_S | B_COST | -0.00367 | -0.273 | 17.4 | 0 | -0.00444 | -0.256 | 17.5 | 0 |
| B_TIME_S | B_TIME | -0.0233 | -0.842 | 15.7 | 0 | -0.0209 | -0.828 | 16.6 | 0 |
Smallest eigenvalue: 16.4195
Largest eigenvalue: 1005.95
Condition number: 61.2655