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Sun Dec 25 21:20:30 2011
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 log 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 Multinomial Logit |
Number of draws: | 100000 |
Number of estimated parameters: | 5 |
Number of observations: | 6768 |
Number of individuals: | 6768 |
Null log-likelihood: | -6964.663 |
Init log-likelihood: | -5836.619 |
Final log-likelihood: | -5231.403 |
Likelihood ratio test: | 3466.520 |
Rho-square: | 0.249 |
Adjusted rho-square: | 0.248 |
Final gradient norm: | +1.069e-03 |
Diagnostic: | Normal termination. Obj: 6.05545e-06 Const: 6.05545e-06 |
Iterations: | 16 |
Run time: | 15h 55:19 |
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 | 0.174 | 0.0582 | 3.00 | 0.00 | 0.0627 | 2.78 | 0.01 | ||
ASC_SM | 0.00 | fixed | |||||||
ASC_TRAIN | -0.346 | 0.0676 | -5.12 | 0.00 | 0.0733 | -4.72 | 0.00 | ||
B_COST | -1.38 | 0.0746 | -18.51 | 0.00 | 0.0979 | -14.11 | 0.00 | ||
B_TIME | 0.575 | 0.0653 | 8.81 | 0.00 | 0.0713 | 8.07 | 0.00 | ||
B_TIME_S | 1.24 | 0.103 | 12.03 | 0.00 | 0.133 | 9.32 | 0.00 |
Id | Name | Availability | Specification |
---|---|---|---|
1 | A1_TRAIN | TRAIN_AV_SP | ASC_TRAIN * one + B_COST * TRAIN_COST_SCALED + -(exp(B_TIME [ B_TIME_S ] )) * TRAIN_TT_SCALED |
2 | A2_SM | SM_AV | ASC_SM * one + B_COST * SM_COST_SCALED + -(exp(B_TIME [ B_TIME_S ] )) * SM_TT_SCALED |
3 | A3_Car | CAR_AV_SP | ASC_CAR * one + B_COST * CAR_CO_SCALED + -(exp(B_TIME [ B_TIME_S ] )) * CAR_TT_SCALED |
Name | Value | Std err | t-test | Robust Std err | Robust t-test |
---|---|---|---|---|---|
B_TIME_B_TIME_S | 1.54 | 0.255 | 6.01 |
Coefficient1 | Coefficient2 | Covariance | Correlation | t-test | p-value | Rob. cov. | Rob. corr. | Rob. t-test | p-value | ||
---|---|---|---|---|---|---|---|---|---|---|---|
B_TIME | B_TIME_S | 0.000600 | 0.0892 | -5.68 | 0.00 | 0.000368 | 0.0388 | -4.47 | 0.00 | ||
ASC_CAR | B_TIME | 0.00261 | 0.687 | -8.15 | 0.00 | 0.00313 | 0.699 | -7.63 | 0.00 | ||
ASC_TRAIN | B_COST | -0.000691 | -0.137 | 9.64 | 0.00 | -0.00130 | -0.181 | 7.81 | 0.00 | ||
ASC_CAR | B_TIME_S | 0.00152 | 0.254 | -10.18 | 0.00 | 0.00238 | 0.285 | -8.20 | 0.00 | ||
ASC_CAR | ASC_TRAIN | 0.00276 | 0.703 | 10.56 | 0.00 | 0.00346 | 0.752 | 10.64 | 0.00 | ||
ASC_TRAIN | B_TIME_S | 0.000445 | 0.0638 | -13.26 | 0.00 | 0.000193 | 0.0198 | -10.53 | 0.00 | ||
ASC_CAR | B_COST | -0.000372 | -0.0857 | 15.79 | 0.00 | -0.00107 | -0.174 | 12.43 | 0.00 | ||
B_COST | B_TIME | -0.00156 | -0.321 | -17.19 | 0.00 | -0.00281 | -0.403 | -13.74 | 0.00 | ||
B_COST | B_TIME_S | -0.00270 | -0.351 | -17.84 | 0.00 | -0.00460 | -0.353 | -13.72 | 0.00 | ||
ASC_TRAIN | B_TIME | 0.00341 | 0.773 | -20.54 | 0.00 | 0.00418 | 0.801 | -20.20 | 0.00 |
Smallest singular value of the hessian: 5.86868