3: MTC MNL Mode Choice, Zeroed Shared

d = larch.examples.MTC()
m = larch.Model(dataservice=d)

Model 3 posits the effect of income on all the automobile modes (drive alone, shared ride 2, and shared ride 3+) is the same, but the effect is different for the other modes. We include this constraint by setting the income coefficients in the utilities of the automobile modes to be equal. In this case, we set them to zero since drive alone is the reference mode. (pp. 108)

We set the terms to zero can be done by omitting the terms altogether.

from larch.roles import P, X, PX
m.utility_co[2] = P("ASC_SR2")
m.utility_co[3] = P("ASC_SR3P")
m.utility_co[4] = P("ASC_TRAN") + P("hhinc#4") * X("hhinc")
m.utility_co[5] = P("ASC_BIKE") + P("hhinc#5") * X("hhinc")
m.utility_co[6] = P("ASC_WALK") + P("hhinc#6") * X("hhinc")
m.utility_ca = PX("tottime") + PX("totcost")
m.availability_var = '_avail_'
m.choice_ca_var = '_choice_'
m.ordering = (
        ("LOS", "totcost", "tottime", ),
        ("Income", "hhinc.*", ),
        ("ASCs", "ASC.*", ),
)
m.title = "MTC Example 3, Zeroed Shared"
>>> m.load_data()
>>> m.maximize_loglike()
┣ ...Optimization terminated successfully...
>>> m.calculate_parameter_covariance()
>>> m.loglike()
-3627.233...

>>> print(m.pfo()[['value','std err','t stat','robust std err','robust t stat']])
                     value  std err   t stat  robust std err  robust t stat
Category Parameter
LOS      totcost   -0.0049   0.0002 -20.6062          0.0003       -17.3891
         tottime   -0.0513   0.0031 -16.5594          0.0035       -14.8580
Income   hhinc#4   -0.0049   0.0018  -2.7295          0.0018        -2.7644
         hhinc#5   -0.0125   0.0053  -2.3451          0.0065        -1.9014
         hhinc#6   -0.0093   0.0030  -3.0977          0.0032        -2.9143
ASCs     ASC_BIKE  -2.3981   0.3038  -7.8934          0.3600        -6.6622
         ASC_SR2   -2.3043   0.0547 -42.1387          0.0574       -40.1180
         ASC_SR3P  -3.7036   0.0930 -39.8127          0.0950       -38.9751
         ASC_TRAN  -0.6975   0.1304  -5.3504          0.1277        -5.4600
         ASC_WALK  -0.2292   0.1933  -1.1857          0.2057        -1.1141