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 10:38:20.123322
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: | 14nestedEndogenousSampling.html |
Database name: | swissmetro |
Number of estimated parameters: | 5 |
Sample size: | 6768 |
Excluded observations: | 3960 |
Init log likelihood: | -14995.62 |
Final log likelihood: | -5202.916 |
Likelihood ratio test for the init. model: | 19585.42 |
Rho-square for the init. model: | 0.653 |
Rho-square-bar for the init. model: | 0.653 |
Akaike Information Criterion: | 10415.83 |
Bayesian Information Criterion: | 10449.93 |
Final gradient norm: | 2.4883E-02 |
Nbr of threads: | 36 |
Algorithm: | BFGS with trust region for simple bound constraints |
Proportion analytical hessian: | 0.0% |
Relative projected gradient: | 1.716115e-06 |
Number of iterations: | 26 |
Number of function evaluations: | 77 |
Number of gradient evaluations: | 26 |
Number of hessian evaluations: | 0 |
Cause of termination: | Relative gradient = 1.7e-06 <= 6.1e-06 |
Optimization time: | 0:00:00.345494 |
Name | Value | Std err | t-test | p-value | Rob. Std err | Rob. t-test | Rob. p-value |
---|---|---|---|---|---|---|---|
ASC_CAR | -1.13 | 0.0423 | -26.7 | 0 | 0.0606 | -18.6 | 0 |
ASC_TRAIN | -2.77 | 0.0539 | -51.4 | 0 | 0.0805 | -34.4 | 0 |
B_COST | -0.999 | 0.0472 | -21.2 | 0 | 0.0641 | -15.6 | 0 |
B_TIME | -0.975 | 0.055 | -17.7 | 0 | 0.111 | -8.8 | 0 |
MU | 1.63 | 0.0541 | 30.1 | 0 | 0.0627 | 26 | 0 |
Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | Rob. p-value |
---|---|---|---|---|---|---|---|---|---|
ASC_TRAIN | ASC_CAR | 0.000926 | 0.406 | -30.8 | 0 | 0.00326 | 0.667 | -27.2 | 0 |
B_COST | ASC_CAR | 0.000292 | 0.146 | 2.19 | 0.0288 | -0.000206 | -0.0529 | 1.41 | 0.157 |
B_COST | ASC_TRAIN | 0.000446 | 0.175 | 27.2 | 0 | -0.000502 | -0.0971 | 16.4 | 0 |
B_TIME | ASC_CAR | -0.00146 | -0.626 | 1.74 | 0.082 | -0.00559 | -0.832 | 0.928 | 0.353 |
B_TIME | ASC_TRAIN | -0.00109 | -0.369 | 19.9 | 0 | -0.00645 | -0.723 | 10.1 | 0 |
B_TIME | B_COST | 0.00058 | 0.223 | 0.387 | 0.698 | 0.00245 | 0.345 | 0.231 | 0.817 |
MU | ASC_CAR | -0.00078 | -0.341 | 34.8 | 0 | -0.00138 | -0.362 | 27.1 | 0 |
MU | ASC_TRAIN | 0.00146 | 0.502 | 81.7 | 0 | 0.00153 | 0.303 | 51.3 | 0 |
MU | B_COST | 0.00041 | 0.161 | 40 | 0 | 0.000308 | 0.0767 | 30.5 | 0 |
MU | B_TIME | 0.00117 | 0.392 | 43.3 | 0 | 0.00212 | 0.305 | 23.8 | 0 |
Smallest eigenvalue: 195.402
Largest eigenvalue: 3071.11
Condition number: 15.7169