biogeme 3.2.6 [2020-06-03]
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 2020-06-03 09:17:48.575098
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Report file: | 05normalMixture_allAlgos_scipy.html |
Database name: | swissmetro |
Number of estimated parameters: | 5 |
Sample size: | 6768 |
Excluded observations: | 3960 |
Init log likelihood: | -6879.615 |
Final log likelihood: | -5214.908 |
Likelihood ratio test for the init. model: | 3329.414 |
Rho-square for the init. model: | 0.242 |
Rho-square-bar for the init. model: | 0.241 |
Akaike Information Criterion: | 10439.82 |
Bayesian Information Criterion: | 10473.92 |
Final gradient norm: | 2.8382E-04 |
Number of draws: | 100000 |
Draws generation time: | 0:15:50.694502 |
Types of draws: | ['B_TIME_RND: NORMAL'] |
Nbr of threads: | 36 |
Algorithm: | scipy.optimize |
Cause of termination: | b'CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL' |
Number of iterations: | 15 |
Number of function evaluations: | 16 |
Optimization time: | 0:42:05.669568 |
Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
---|---|---|---|---|---|---|---|
ASC_CAR | 0.137 | 0.0516 | 2.65 | 0.00798 | 0.0517 | 2.65 | 0.0081 |
ASC_TRAIN | -0.402 | 0.0634 | -6.34 | 2.35e-10 | 0.0658 | -6.11 | 1.01e-09 |
B_COST | -1.29 | 0.063 | -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 | 0.0562 | -18 | 0 | 0.000128 | 0.0286 | -14.3 | 0 |
B_COST | ASC_TRAIN | -0.000138 | -0.0345 | -9.71 | 0 | -0.000305 | -0.0536 | -7.94 | 2e-15 |
B_TIME | ASC_CAR | -0.00394 | -0.642 | -15.2 | 0 | -0.00386 | -0.637 | -15.4 | 0 |
B_TIME | ASC_TRAIN | -0.00456 | -0.604 | -11.2 | 0 | -0.0047 | -0.61 | -11.2 | 0 |
B_TIME | B_COST | 0.00238 | 0.317 | -8.42 | 0 | 0.00373 | 0.369 | -8.33 | 0 |
B_TIME_S | ASC_CAR | 0.00298 | 0.417 | 12.1 | 0 | 0.00284 | 0.417 | 12.7 | 0 |
B_TIME_S | ASC_TRAIN | 0.00182 | 0.208 | 14.7 | 0 | 0.00146 | 0.169 | 15.1 | 0 |
B_TIME_S | B_COST | -0.00258 | -0.296 | 17.5 | 0 | -0.00322 | -0.283 | 16.7 | 0 |
B_TIME_S | B_TIME | -0.0127 | -0.774 | 16.2 | 0 | -0.0114 | -0.741 | 16.9 | 0 |
Smallest eigenvalue: 31.5971
Largest eigenvalue: 1001.23
Condition number: 31.6874