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 13:20:53.836621
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: | 25triangularMixture.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6941.996 |
| Final log likelihood: | -5214.262 |
| Likelihood ratio test for the init. model: | 3455.468 |
| Rho-square for the init. model: | 0.249 |
| Rho-square-bar for the init. model: | 0.248 |
| Akaike Information Criterion: | 10438.52 |
| Bayesian Information Criterion: | 10472.62 |
| Final gradient norm: | 1.7773E-02 |
| Number of draws: | 100000 |
| Draws generation time: | 0:12:14.422488 |
| Types of draws: | ['B_TIME_RND: TRIANGULAR'] |
| Nbr of threads: | 36 |
| Algorithm: | BFGS with trust region for simple bound constraints |
| Proportion analytical hessian: | 0.0% |
| Relative projected gradient: | 5.811271e-06 |
| Number of iterations: | 31 |
| Number of function evaluations: | 94 |
| Number of gradient evaluations: | 32 |
| Number of hessian evaluations: | 0 |
| Cause of termination: | Relative gradient = 5.8e-06 <= 6.1e-06 |
| Optimization time: | 2:25:15.282339 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.141 | 0.0518 | 2.72 | 0.00647 | 0.0521 | 2.71 | 0.00676 |
| ASC_TRAIN | -0.393 | 0.0635 | -6.19 | 6.04e-10 | 0.0657 | -5.98 | 2.22e-09 |
| B_COST | -1.28 | 0.0628 | -20.4 | 0 | 0.0863 | -14.8 | 0 |
| B_TIME | -2.28 | 0.121 | -18.8 | 0 | 0.119 | -19.1 | 0 |
| B_TIME_S | 3.99 | 0.321 | 12.4 | 0 | 0.305 | 13.1 | 0 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | ASC_CAR | 0.00207 | 0.63 | -10.5 | 0 | 0.00226 | 0.661 | -10.7 | 0 |
| B_COST | ASC_CAR | 0.000187 | 0.0575 | -18 | 0 | 0.000145 | 0.0323 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.000143 | -0.0358 | -9.78 | 0 | -0.000301 | -0.0532 | -7.99 | 1.33e-15 |
| B_TIME | ASC_CAR | -0.00405 | -0.646 | -15.2 | 0 | -0.00401 | -0.646 | -15.3 | 0 |
| B_TIME | ASC_TRAIN | -0.00471 | -0.614 | -11.2 | 0 | -0.00486 | -0.621 | -11.2 | 0 |
| B_TIME | B_COST | 0.00233 | 0.307 | -8.44 | 0 | 0.00363 | 0.354 | -8.3 | 0 |
| B_TIME_S | ASC_CAR | 0.00722 | 0.433 | 12.7 | 0 | 0.00708 | 0.445 | 13.5 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00483 | 0.237 | 14 | 0 | 0.00419 | 0.209 | 14.7 | 0 |
| B_TIME_S | B_COST | -0.00579 | -0.287 | 15.3 | 0 | -0.00715 | -0.271 | 15.6 | 0 |
| B_TIME_S | B_TIME | -0.0306 | -0.788 | 14.8 | 0 | -0.0277 | -0.763 | 15.5 | 0 |
Smallest eigenvalue: 8.75867
Largest eigenvalue: 996.372
Condition number: 113.758