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 15:53:24.444691
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| Report file: | 07estimationMonteCarlo_mlhs_anti_500.html |
| Database name: | swissmetro |
| Number of estimated parameters: | 5 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6878.95 |
| Final log likelihood: | -5216.191 |
| Likelihood ratio test for the init. model: | 3325.519 |
| Rho-square for the init. model: | 0.242 |
| Rho-square-bar for the init. model: | 0.241 |
| Akaike Information Criterion: | 10442.38 |
| Bayesian Information Criterion: | 10476.48 |
| Final gradient norm: | 2.1416E-02 |
| Number of draws: | 500 |
| Draws generation time: | 0:00:05.306359 |
| Types of draws: | ['B_TIME_RND: NORMAL_MLHS_ANTI'] |
| Nbr of threads: | 36 |
| Algorithm: | Newton with trust region for simple bound constraints |
| Relative projected gradient: | 3.886535e-06 |
| Number of iterations: | 7 |
| Number of function evaluations: | 22 |
| Number of gradient evaluations: | 8 |
| Number of hessian evaluations: | 8 |
| Cause of termination: | Relative gradient = 3.9e-06 <= 6.1e-06 |
| Optimization time: | 0:00:18.502697 |
| Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.133 | 0.0515 | 2.58 | 0.00976 | 0.0515 | 2.58 | 0.00979 |
| ASC_TRAIN | -0.404 | 0.0632 | -6.39 | 1.68e-10 | 0.0654 | -6.17 | 6.88e-10 |
| B_COST | -1.28 | 0.0628 | -20.4 | 0 | 0.086 | -14.9 | 0 |
| B_TIME | -2.24 | 0.117 | -19.1 | 0 | 0.115 | -19.4 | 0 |
| B_TIME_S | 1.63 | 0.134 | 12.1 | 0 | 0.125 | 13 | 0 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value |
|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | ASC_CAR | 0.00203 | 0.625 | -10.6 | 0 | 0.00222 | 0.658 | -10.7 | 0 |
| B_COST | ASC_CAR | 0.000189 | 0.0584 | -17.9 | 0 | 0.000132 | 0.0298 | -14.3 | 0 |
| B_COST | ASC_TRAIN | -0.00015 | -0.0377 | -9.68 | 0 | -0.000333 | -0.0592 | -7.91 | 2.66e-15 |
| B_TIME | ASC_CAR | -0.00388 | -0.642 | -15.3 | 0 | -0.00378 | -0.636 | -15.5 | 0 |
| B_TIME | ASC_TRAIN | -0.00454 | -0.612 | -11.2 | 0 | -0.0047 | -0.623 | -11.2 | 0 |
| B_TIME | B_COST | 0.00232 | 0.315 | -8.38 | 0 | 0.00367 | 0.37 | -8.3 | 0 |
| B_TIME_S | ASC_CAR | 0.0029 | 0.42 | 12.3 | 0 | 0.00273 | 0.424 | 13.2 | 0 |
| B_TIME_S | ASC_TRAIN | 0.00189 | 0.223 | 15.1 | 0 | 0.00163 | 0.199 | 15.7 | 0 |
| B_TIME_S | B_COST | -0.00246 | -0.292 | 17.8 | 0 | -0.00307 | -0.285 | 17 | 0 |
| B_TIME_S | B_TIME | -0.0122 | -0.774 | 16.3 | 0 | -0.0107 | -0.745 | 17.2 | 0 |
Smallest eigenvalue: 32.939
Largest eigenvalue: 1004.89
Condition number: 30.5077