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Wed Jul 6 20:12:18 2016
Tip: click on the columns headers to sort a table [Credits]
| Example of a mixture of logit model with panel data for a transportation mode choice with 3 alternatives: |
| - Train |
| - Car |
| - Swissmetro, an hypothetical high-speed train |
| The time coefficient is normally distributed. 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 square brackets are associated with a normal distribution. |
| Model: | Mixed Logit for panel data |
| Number of Hess-Train draws: | 500 |
| Number of estimated parameters: | 5 |
| Number of observations: | 6768 |
| Number of individuals: | 752 |
| Null log likelihood: | -6964.663 |
| Init log likelihood: | -6964.663 |
| Final log likelihood: | -4359.797 |
| Likelihood ratio test: | 5209.732 |
| Rho-square: | 0.374 |
| Adjusted rho-square: | 0.373 |
| Final gradient norm: | +1.725e-05 |
| Diagnostic: | Normal termination. Obj: 6.05545e-06 Const: 6.05545e-06 |
| Iterations: | 23 |
| Run time: | 04:50 |
| 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 | 0.281 | 0.0567 | 4.96 | 0.00 | 0.108 | 2.61 | 0.01 | ||
| ASC_SM | 0.00 | fixed | |||||||
| ASC_TRAIN | -0.575 | 0.0819 | -7.03 | 0.00 | 0.146 | -3.95 | 0.00 | ||
| B_COST | -1.65 | 0.0775 | -21.30 | 0.00 | 0.291 | -5.66 | 0.00 | ||
| B_TIME | -3.22 | 0.188 | -17.11 | 0.00 | 0.223 | -14.45 | 0.00 | ||
| B_TIME_S | 3.64 | 0.174 | 20.92 | 0.00 | 0.242 | 15.04 | 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 | 13.2 | 1.26 | 10.46 |
| Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | p-value | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ASC_TRAIN | B_COST | 0.000764 | 0.120 | 10.17 | 0.00 | 0.00721 | 0.170 | 3.55 | 0.00 | ||
| B_COST | B_TIME | 0.00176 | 0.121 | 8.06 | 0.00 | 0.0220 | 0.339 | 5.22 | 0.00 | ||
| ASC_CAR | B_COST | 0.000738 | 0.168 | 21.96 | 0.00 | 0.00381 | 0.121 | 6.48 | 0.00 | ||
| ASC_CAR | ASC_TRAIN | 0.00290 | 0.626 | 13.36 | 0.00 | 0.00901 | 0.576 | 7.06 | 0.00 | ||
| ASC_TRAIN | B_TIME | -0.00660 | -0.428 | 11.25 | 0.00 | -0.0152 | -0.469 | 8.31 | 0.00 | ||
| ASC_CAR | B_TIME | -0.00437 | -0.410 | 16.09 | 0.00 | -0.0112 | -0.466 | 12.12 | 0.00 | ||
| B_COST | B_TIME_S | -0.00234 | -0.174 | -26.15 | 0.00 | -0.0209 | -0.297 | -12.29 | 0.00 | ||
| ASC_CAR | B_TIME_S | 0.00119 | 0.120 | -19.04 | 0.00 | 0.00319 | 0.123 | -13.30 | 0.00 | ||
| ASC_TRAIN | B_TIME_S | -0.000827 | -0.0581 | -21.45 | 0.00 | -0.000174 | -0.00495 | -14.89 | 0.00 | ||
| B_TIME | B_TIME_S | -0.0105 | -0.321 | -23.30 | 0.00 | -0.0244 | -0.453 | -17.31 | 0.00 |
Smallest singular value of the hessian: 5.02662