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Tue Apr 18 19:04:47 2017
Tip: click on the columns headers to sort a table [Credits]
| Example of a logit model for a transportation mode choice with 3 alternatives: |
| - Train |
| - Car |
| - Swissmetro, an hypothetical high-speed train |
| The time coefficient is distributed, with a unifrom distribution. This is an example of a mixture of logit model. |
| The syntax for a distributed coefficient is B_TIME { B_TIME_S }, where |
| B_TIME is the mean and B_TIME_S squared is the variance. |
| The curly brackets are associated with a uniform distribution. |
| Model: | Mixed Logit |
| Number of Hess-Train draws: | 500 |
| Number of estimated parameters: | 5 |
| Number of observations: | 6768 |
| Number of individuals: | 6768 |
| Null log likelihood: | -6964.663 |
| Init log likelihood: | -6964.663 |
| Final log likelihood: | -5215.027 |
| Likelihood ratio test: | 3499.272 |
| Rho-square: | 0.251 |
| Adjusted rho-square: | 0.250 |
| Final gradient norm: | +1.056e-03 |
| Diagnostic: | Normal termination. Obj: 6.05545e-06 Const: 6.05545e-06 |
| Iterations: | 18 |
| Run time: | 01:16 |
| Variance-covariance: | from finite difference hessian |
| Sample file: | ../swissmetro.dat |
| Name | Value | Std err | t-test | p-value | Robust Std err | Robust t-test | p-value | ||
|---|---|---|---|---|---|---|---|---|---|
| ASC_CAR | 0.145 | 0.0527 | 2.75 | 0.01 | 0.0533 | 2.72 | 0.01 | ||
| ASC_SM | 0.00 | fixed | |||||||
| ASC_TRAIN | -0.385 | 0.0639 | -6.03 | 0.00 | 0.0660 | -5.83 | 0.00 | ||
| B_COST | -1.28 | 0.0627 | -20.37 | 0.00 | 0.0866 | -14.75 | 0.00 | ||
| B_TIME | -2.32 | 0.129 | -18.02 | 0.00 | 0.126 | -18.40 | 0.00 | ||
| B_TIME_S | 2.88 | 0.215 | 13.40 | 0.00 | 0.200 | 14.38 | 0.00 |
| Id | Name | Availability | Specification |
|---|---|---|---|
| 1 | A1_TRAIN | TRAIN_AV_SP | ASC_TRAIN * one + B_TIME { B_TIME_S } * TRAIN_TT_SCALED + B_COST * TRAIN_COST_SCALED |
| 2 | A2_SM | SM_AV | ASC_SM * one + B_TIME { B_TIME_S } * SM_TT_SCALED + B_COST * SM_COST_SCALED |
| 3 | A3_Car | CAR_AV_SP | ASC_CAR * one + B_TIME { B_TIME_S } * CAR_TT_SCALED + B_COST * CAR_CO_SCALED |
| Name | Value | Std err | t-test | Robust Std err | Robust t-test |
|---|---|---|---|---|---|
| B_TIME_B_TIME_S | 2.76 | 0.412 | 6.70 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | p-value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | B_COST | -0.000182 | -0.0455 | 9.75 | 0.00 | -0.000319 | -0.0558 | 7.99 | 0.00 | ||
| B_COST | B_TIME | 0.00234 | 0.290 | 8.28 | 0.00 | 0.00353 | 0.323 | 8.16 | 0.00 | ||
| ASC_CAR | ASC_TRAIN | 0.00218 | 0.649 | 10.64 | 0.00 | 0.00241 | 0.685 | 10.87 | 0.00 | ||
| ASC_TRAIN | B_TIME | -0.00531 | -0.645 | 10.94 | 0.00 | -0.00549 | -0.660 | 10.95 | 0.00 | ||
| ASC_CAR | B_COST | 0.000184 | 0.0558 | 17.87 | 0.00 | 0.000172 | 0.0373 | 14.23 | 0.00 | ||
| ASC_CAR | B_TIME | -0.00446 | -0.657 | 14.66 | 0.00 | -0.00446 | -0.663 | 14.83 | 0.00 | ||
| ASC_CAR | B_TIME_S | 0.00555 | 0.491 | -14.06 | 0.00 | 0.00551 | 0.517 | -15.31 | 0.00 | ||
| B_TIME | B_TIME_S | -0.0233 | -0.842 | -15.72 | 0.00 | -0.0209 | -0.827 | -16.63 | 0.00 | ||
| ASC_TRAIN | B_TIME_S | 0.00475 | 0.347 | -16.18 | 0.00 | 0.00455 | 0.344 | -17.37 | 0.00 | ||
| B_COST | B_TIME_S | -0.00367 | -0.273 | -17.35 | 0.00 | -0.00444 | -0.256 | -17.49 | 0.00 |
Smallest singular value of the hessian: 5.30238