9: MTC MNL Mode Choice, TTR = 4.0

Model 9 is formulated the same way as Model 8, only with the TTR set to 4. (pp. 114)

d = larch.examples.MTC()
m = larch.Model(dataservice=d)
from larch.roles import P, X, PX
m.utility_co[2] = P("ASC_SR2")  + P("hhinc#2,3") * X("hhinc")
m.utility_co[3] = P("ASC_SR3P") + P("hhinc#2,3") * X("hhinc")
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 = (
         + P("nonmotorized_time") * X("(altnum>4) * tottime")
         + P("motorized_time") * (X("(altnum <= 4) * ivtt")
         + 4 * X("(altnum <= 4) * ovtt")) + PX("totcost")
         )
m.availability_var = '_avail_'
m.choice_ca_var = '_choice_'
m.ordering = (
        ("LOS", ".*cost.*", ".*time.*", ".*ivtt.*", ),
        ("Income", "hhinc.*", ),
        ("ASCs", "ASC.*", ),
)
>>> m.load_data()
>>> m.maximize_loglike()
┣ ...Optimization terminated successfully...
>>> m.calculate_parameter_covariance()
>>> m.loglike()
-3590.916...

>>> 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           -0.0048   0.0002 -20.3016          0.0003       -17.0773
         motorized_time    -0.0173   0.0013 -13.6780          0.0014       -12.2046
         nonmotorized_time -0.0652   0.0053 -12.3235          0.0053       -12.2437
Income   hhinc#2,3         -0.0016   0.0014  -1.1304          0.0015        -1.0462
         hhinc#4           -0.0056   0.0018  -3.0211          0.0018        -3.1421
         hhinc#5           -0.0123   0.0052  -2.3445          0.0063        -1.9483
         hhinc#6           -0.0094   0.0031  -3.0885          0.0032        -2.9163
ASCs     ASC_BIKE          -1.7748   0.3232  -5.4910          0.3693        -4.8052
         ASC_SR2           -2.3642   0.0969 -24.4032          0.1055       -22.4135
         ASC_SR3P          -3.7992   0.1222 -31.0899          0.1276       -29.7836
         ASC_TRAN          -0.5270   0.1479  -3.5636          0.1469        -3.5866
         ASC_WALK           0.4292   0.2526   1.6989          0.2583         1.6613