19: MTC Private Auto Nested Mode Choice
19: MTC Private Auto Nested Mode Choice¶
m = larch.example(17)
Model 19’s nesting structure groups all private automobile alternatives. (pp. 176)
private_auto = m.graph.new_node(parameter='mu', children=[1,2,3], name='Motorized')
m.unmangle(True)
m.set_value('mu',maximum=2.0)
m.ordering = (
("CostbyInc","costbyincome",),
("TravelTime",".*time.*",".*dist.*", ),
("Household","hhinc.*","vehbywrk.*",),
("Zonal","wkcbd.*","wkempden.*",),
("ASCs","ASC.*",),
)
>>> m.load_data()
>>> m.maximize_loglike(method='bhhh')
┣ ...Optimization terminated successfully...
>>> m.loglike()
-3435.995...
>>> print(m.pfo()[['value']])
value
Category Parameter
CostbyInc costbyincome -0.0607
TravelTime motorized_time -0.0202
nonmotorized_time -0.0462
motorized_ovtbydist -0.1358
Household hhinc#4 -0.0045
hhinc#5 -0.0074
hhinc#6 -0.0050
vehbywrk_BIKE -0.6107
vehbywrk_SR -0.5121
vehbywrk_TRANSIT -0.8725
vehbywrk_WALK -0.6143
Zonal wkcbd_BIKE 0.5234
wkcbd_SR2 0.3982
wkcbd_SR3 1.5869
wkcbd_TRANSIT 1.3667
wkcbd_WALK 0.1170
wkempden_BIKE 0.0023
wkempden_SR2 0.0024
wkempden_SR3 0.0036
wkempden_TRANSIT 0.0035
wkempden_WALK 0.0033
ASCs ASC_BIKE -1.8205
ASC_SR2 -2.5667
ASC_SR3 -4.9623
ASC_TRANSIT -0.8474
ASC_WALK -0.1166
Other mu 1.4656