biogeme 2.6a [Mon Apr 17 15:33:55 CEST 2017]
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Michel Bierlaire, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne (EPFL)
This file has automatically been generated on Tue Apr 18 19:56:20 2017
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: | 14selectionBias.html |
| Sample file: | __bin_swissmetro.dat |
| Car utility: | ASC_CAR + B_TIME * CAR_TT_SCALED + B_COST * CAR_CO_SCALED |
| Swissmetro utility: | ASC_SM + B_TIME * SM_TT_SCALED + B_COST * SM_COST_SCALED |
| Train utility: | ASC_TRAIN + B_TIME * TRAIN_TT_SCALED + B_COST * TRAIN_COST_SCALED |
| Alt. 1 available: | 6768 |
| Alt. 1 chosen: | 908 |
| Alt. 2 available: | 6768 |
| Alt. 2 chosen: | 4090 |
| Alt. 3 available: | 5607 |
| Alt. 3 chosen: | 1770 |
| Cte loglikelihood (only for full choice sets): | -6257.86 |
| Null loglikelihood: | -6964.66 |
| Number of estimated parameters: | 6 |
| Sample size: | 6768 |
| Excluded observations: | 3960 |
| Init log likelihood: | -6964.663 |
| Final log likelihood: | -5169.642 |
| Likelihood ratio test for the init. model: | 3590.043 |
| Rho-square for the init. model: | 0.258 |
| Rho-square-bar for the init. model: | 0.257 |
| Akaike Information Criterion: | 10351.283 |
| Bayesian Information Criterion: | 10392.203 |
| Final gradient norm: | +1.247e-04 |
| Diagnostic: | Trust region algorithm with simple bounds (CGT2000): Convergence reached... |
| Iterations: | 25 |
| Data processing time: | 00:00 |
| Run time: | 00:02 |
| Nbr of threads: | 12 |
Click on the headers of the columns to sort the table [Credits]
| Name | Value | Std err | t-test | p-value | Robust Std err | Robust t-test | p-value | ||
|---|---|---|---|---|---|---|---|---|---|
| ASC_CAR | -0.317 | 0.0443 | -7.16 | 0.00 | 0.0597 | -5.31 | 0.00 | ||
| ASC_TRAIN | -10.2 | 3.13 | -3.27 | 0.00 | 3.15 | -3.25 | 0.00 | ||
| B_COST | -1.11 | 0.0511 | -21.65 | 0.00 | 0.0672 | -16.46 | 0.00 | ||
| B_TIME | -1.13 | 0.0576 | -19.59 | 0.00 | 0.103 | -10.91 | 0.00 | ||
| MU | 1.14 | 0.0459 | 24.94 | 0.00 | 0.0465 | 24.60 | 0.00 | ||
| SB_TRAIN | 10.4 | 3.15 | 3.31 | 0.00 | 3.16 | 3.29 | 0.00 |
Click on the headers of the columns to sort the table [Credits]
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | p-value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| B_COST | B_TIME | 0.000521 | 0.177 | 0.30 | 0.76 | * | 0.00183 | 0.264 | 0.20 | 0.84 | * |
| MU | SB_TRAIN | -0.142 | -0.982 | -2.90 | 0.00 | -0.144 | -0.981 | -2.89 | 0.00 | ||
| ASC_TRAIN | B_COST | 0.00708 | 0.0443 | -2.92 | 0.00 | -0.0323 | -0.153 | -2.89 | 0.00 | ||
| ASC_TRAIN | B_TIME | 0.0485 | 0.269 | -2.93 | 0.00 | 0.0283 | 0.0869 | -2.90 | 0.00 | ||
| ASC_CAR | ASC_TRAIN | -0.0268 | -0.193 | 3.16 | 0.00 | -0.0319 | -0.169 | 3.14 | 0.00 | ||
| ASC_TRAIN | SB_TRAIN | -9.84 | -1.00 | -3.29 | 0.00 | -9.94 | -1.00 | -3.27 | 0.00 | ||
| ASC_CAR | SB_TRAIN | 0.0278 | 0.199 | -3.42 | 0.00 | 0.0348 | 0.185 | -3.41 | 0.00 | ||
| B_TIME | SB_TRAIN | -0.0505 | -0.279 | -3.65 | 0.00 | -0.0345 | -0.106 | -3.64 | 0.00 | ||
| B_COST | SB_TRAIN | -0.00716 | -0.0445 | -3.66 | 0.00 | 0.0316 | 0.149 | -3.66 | 0.00 | ||
| ASC_TRAIN | MU | 0.141 | 0.984 | -3.69 | 0.00 | 0.144 | 0.983 | -3.67 | 0.00 | ||
| ASC_CAR | B_TIME | -0.00155 | -0.607 | 8.86 | 0.00 | -0.00498 | -0.806 | 5.21 | 0.00 | ||
| ASC_CAR | B_COST | 0.000508 | 0.224 | 13.23 | 0.00 | 0.000243 | 0.0605 | 9.06 | 0.00 | ||
| ASC_CAR | MU | -0.000484 | -0.238 | -20.60 | 0.00 | -0.000657 | -0.236 | -17.41 | 0.00 | ||
| B_TIME | MU | 0.000782 | 0.296 | -36.59 | 0.00 | 0.000690 | 0.143 | -21.22 | 0.00 | ||
| B_COST | MU | 7.79e-05 | 0.0332 | -33.32 | 0.00 | -0.000489 | -0.156 | -25.72 | 0.00 |
Smallest singular value: 0.050512