Brian
Glad that helped.
We have often been able to use household surveys for transportation
planning/modeling effectively as a data source for estimating the
household location choice model, since these residential locations are
generally well geocoded, and increasingly the surveys collect
information on length of residence, and occasionally a geocoded
previous location (a very helpful item, if you can influence a future
survey design).
Paul
On Mar 5, 2008, at 12:53 PM, brian voigt wrote:
> Paul - dropping the constant definitely helps. I'm now able to
> estimate a reasonable model. As for the households for estimation
> data, we're using some household level market segmentation data that
> was purchased from Claritas. This data set includes some of the
> basic (age of head, income, presence of children) information that
> we're likely to need for estimation. This is different from our
> synthesized households. Unfortunately the data does not indicate how
> long households have lived in their current location, but based on
> my observation seems better to use than the synthetic households
> because the relationship between age, etc and the household location
> is more accurate than the information generated in the household
> synthesis and assignment process.
>
> In reading your 2006 paper "Reconciling household residential
> location choices ..." you mention the use of household level
> surveys. Was this part of a trip diary survey or simply a household
> level survey targeted at recent movers? Is it possible to see the
> survey questionnaire that was used to collect this data? I'm hoping
> that we can collect more specific household level data in the near
> future.
>
> brian
>
> Paul Waddell wrote:
>>
>> Brian
>>
>> It looks like you're including a constant, which would not be
>> appropriate in a location choice model where the model estimation is
>> using random sampling of alternatives. You can only use alternative-
>> specific constants when you have a small number of alternatives, and
>> they are always in the same order-- like in a mode choice model. Try
>> dropping the constant for starters.
>>
>> Also - I can't tell if you have a survey of households with observed
>> locations, or are sampling from synthetic households. The former is
>> definitely better, especially if you can sample only those who have
>> moved within the past few years.
>>
>> Paul
>>
>> On Feb 29, 2008, at 11:12 AM, brian voigt wrote:
>>
>>
>>> I'm currently working on estimating the Household Location Choice
>>> Model and am having trouble producing a worthwhile result. I'm not
>>> able to get the model to converge no matter the combination of
>>> variables that I have included in the estimation procedure.
>>> Additionally, the convergence statistic is always the same as the
>>> number of observations (even when I change the number of households
>>> represented in the households_for_estimation table). Finally, as can
>>> be seen in the output, the coefficient estimates are all extremely
>>> small (with correspondingly small t-values). Does this indicate that
>>> there is a problem with my households_for_estimation table?
>>>
>>> Perhaps I am confused about the function of the estimation
>>> procedure. I understand that the number of movers and the unplaced
>>> agents are derived by the Household Relocation Model, but how do
>>> these movers and unplaced agents relate to the records in the
>>> households_for_estimation table? More specifically, how can there be
>>> more movers / unplaced agents than there are records in the
>>> households_for_estimation table? Perhaps too I don't understand
>>> correctly what the dependent variable is that we are modeling. I
>>> thought the estimation procedure evaluated the location choice for
>>> each household in the household_for_estimation table compared to the
>>> attributes of the other records in the choice set. Is this correct?
>>>
>>> I've attached the output from an attempt at estimation to help
>>> illustrate my point. Any input / advice would be most appreciated?
>>> brian
>>>
>>> Brian Voigt
>>> Spatial Analysis Lab
>>> University of Vermont
>>> Burlington, VT 05405
>>>
>>> brian.voigt_at_uvm.edu
>>>
>>> C:\myworkspace\chittenden\estimation>python run_estimation.py -c
>>> chittenden.estimation.estimation_config_voigt --use-
>>> trapperkeeper=false
>>> Cache Directory set to: C://urbansim_cache/
>>> chittco_1990_baseyear_cache
>>> Start simulation run: started on Fri Feb 29 13:18:32 2008
>>> random seed = (1,)
>>> Starting simulation for year 1990: started on Fri Feb 29 13:18:32
>>> 2008
>>> Closing log file: C://urbansim_cache/
>>> chittco_1990_baseyear_cache\run_multiprocess.log
>>> Logging to file: C://urbansim_cache/
>>> chittco_1990_baseyear_cache\year_1990_log.txt
>>> Simulate year 1990: started on Fri Feb 29 13:18:32 2008
>>> Creating object
>>> urbansim
>>> .datasets
>>> .vacant_land_and_building_type_dataset
>>> .VacantLandAndBuildingTypeDataset
>>> Creating object
>>> urbansim
>>> .datasets
>>> .development_constraint_dataset.DevelopmentConstraintDataset
>>> Creating object
>>> urbansim.datasets.zone_dataset.ZoneDataset
>>> Creating object
>>> urbansim.datasets.household_dataset.HouseholdDataset
>>> Creating object
>>> urbansim.datasets.gridcell_dataset.GridcellDataset
>>> Creating object urbansim.datasets.job_dataset.JobDataset
>>> Creating object
>>> urbansim.datasets.target_vacancy_dataset.TargetVacancyDataset
>>> Creating object
>>> urbansim.datasets.job_building_type_dataset.JobBuildingTypeDataset
>>> Creating object
>>> urbansim
>>> .datasets
>>> .development_event_history_dataset.DevelopmentEventHistoryDataset
>>> Creating object
>>> urbansim.datasets.rate_dataset.RateDataset
>>> Running Household Relocation Model (from
>>> urbansim.models.agent_relocation_model): started on Fri Feb 29
>>> 13:18:33 2008
>>> compute_probabilities ...
>>> compute_choices ...
>>> Number of movers: 11301
>>> Running Household Relocation Model (from
>>> urbansim.models.agent_relocation_model): completed...4.8 sec
>>> Unplace 941 agents.
>>> Estimating Household Location Choice Model (from
>>> urbansim.models.household_location_choice_model): started on Fri Feb
>>> 29 13:18:38 200
>>>
>>> Number of agents for estimation: 5000
>>> Sampling locations for estimation ...
>>> Sampling done in 1 chunk(s).
>>> Choice set size: 30
>>> Compute variables ...
>>>
>>> urbansim.gridcell.is_in_floodplain.......................0.3 sec
>>>
>>> urbansim.gridcell.ln_distance_to_highway.................0.3 sec
>>>
>>> urbansim.gridcell.ln_residential_units_within_walking_distance
>>>
>>> urbansim.gridcell.residential_units_within_walking_distance....0.6
>>> sec
>>>
>>> urbansim.gridcell.ln_residential_units_within_walking_distance:
>>> completed...0.7 sec
>>>
>>> urbansim.gridcell.ln_total_employment_within_walking_distance
>>>
>>> urbansim.gridcell.total_employment_within_walking_distance
>>>
>>> urbansim.gridcell.number_of_jobs.................0.3 sec
>>>
>>> urbansim.gridcell.total_employment_within_walking_distance:
>>> completed...0.3 sec
>>>
>>> urbansim.gridcell.ln_total_employment_within_walking_distance:
>>> completed...0.3 sec
>>>
>>> urbansim.gridcell.ln_total_population_within_walking_distance
>>>
>>> urbansim.gridcell.total_population_within_walking_distance
>>>
>>> urbansim.gridcell.population.....................0.0 sec
>>>
>>> urbansim.gridcell.total_population_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim.gridcell.ln_total_population_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim.gridcell.number_of_jobs_within_walking_distance....0.1 sec
>>> urbansim.gridcell.percent_SSS_within_walking_distance
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance
>>>
>>> urbansim.gridcell.is_in_development_type_group_SSS....0.7 sec
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance:
>>> completed...0.8 sec
>>>
>>> urbansim.gridcell.percent_SSS_within_walking_distance: completed...
>>> 0.9 sec
>>>
>>> urbansim
>>> .gridcell.percent_high_income_households_within_walking_distance
>>>
>>> urbansim
>>> .gridcell.number_of_high_income_households_within_walking_distance
>>>
>>> urbansim.gridcell.number_of_high_income_households
>>>
>>> urbansim.household.is_high_income............0.0 sec
>>>
>>> urbansim.gridcell.number_of_high_income_households: completed...0.0
>>> sec
>>>
>>> urbansim
>>> .gridcell.number_of_high_income_households_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim.gridcell.number_of_households_within_walking_distance
>>>
>>> urbansim.gridcell.number_of_households...........0.0 sec
>>>
>>> urbansim.gridcell.number_of_households_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim
>>> .gridcell.percent_high_income_households_within_walking_distance:
>>> completed...0.2 sec
>>> urbansim.gridcell.percent_SSS_within_walking_distance
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance
>>>
>>> urbansim.gridcell.is_in_development_type_group_SSS....0.0 sec
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim.gridcell.percent_SSS_within_walking_distance: completed...
>>> 0.1 sec
>>> urbansim.gridcell.percent_SSS_within_walking_distance
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance
>>>
>>> urbansim.gridcell.is_in_development_type_group_SSS....0.0 sec
>>>
>>> urbansim
>>> .gridcell
>>> .number_of_development_type_group_SSS_within_walking_distance:
>>> completed...0.1 sec
>>>
>>> urbansim.gridcell.percent_SSS_within_walking_distance: completed...
>>> 0.1 sec
>>>
>>> urbansim.household.income_category.......................0.0 sec
>>>
>>> urbansim.household.is_without_children...................0.0 sec
>>> urbansim.household_x_gridcell.cost_to_income_ratio
>>> urbansim.gridcell.total_annual_rent
>>>
>>> urbansim.gridcell.total_residential_value........0.6 sec
>>> urbansim.gridcell.total_annual_rent:
>>> completed.......0.6 sec
>>> urbansim.household_x_gridcell.cost_to_income_ratio:
>>> completed...0.6 sec
>>>
>>> urbansim.household_x_gridcell.income_and_year_built......0.3 sec
>>> Estimate ...
>>> submodel: -2
>>> WARNING: Cannot find increase
>>> Akaike's Information Criterion (AIC): 34047.9738166
>>> Number of Iterations: 10
>>> ***********************************************
>>> Log-likelihood is: -17005.9869083
>>> Null Log-likelihood is: -17005.9869083
>>> Likelihood ratio index: 0.0
>>> Adj. likelihood ratio index: -0.00105845077366
>>> Number of observations: 5000
>>> Suggested |t-value| > 2.91842306587
>>> Convergence statistic is: 5000.0
>>> -----------------------------------------------
>>> Coeff_names estimate std err t-
>>> values
>>> D2LAKE -2.20663e-016 0.000496508
>>> -4.4443e-013
>>> constant 9.5983e+015 1.65882e+014
>>> 57.8622
>>> BFLOOD -1.31402e-013 0.242338
>>> -5.42225e-013
>>> BLDHW 8.11058e-015 0.0318991
>>> 2.54257e-013
>>> BLDUW -3.49379e-015 0.0801334
>>> -4.35996e-014
>>> LE_W 2.20441e-015 0.0158806
>>> 1.38812e-013
>>> BP_TW 3.0224e-015 0.0879053
>>> 3.43825e-014
>>> JOBS_WWD -3.68946e-019 8.16678e-006
>>> -4.51764e-014
>>> PCW -6.93212e-018 0.00267387
>>> -2.59254e-015
>>> BPHIW 1.86301e-017 0.00165672
>>> 1.12451e-014
>>> PIW 1.83701e-016 0.00412956
>>> 4.44844e-014
>>> PRW -1.81968e-017 0.00109088
>>> -1.66809e-014
>>> PWATER -5.58252e-016 0.00327898
>>> -1.70252e-013
>>> PWETLA -2.67156e-016 0.00240074
>>> -1.1128e-013
>>> INC_CAT 0.359024 1.84247e+013
>>> 1.94861e-014
>>> NO_KIDS -10.5912 1.78019e+014
>>> -5.94949e-014
>>> COST_INC_RAT 4.78316e-016 0.0382962
>>> 1.24899e-014
>>> INC_YRBLT 1.85108e-022 6.06333e-009
>>> 3.0529e-014
>>> ***********************************************
>>> Elapsed time: 12.9514644907 seconds
>>> Estimating Household Location Choice Model (from
>>> urbansim.models.household_location_choice_model): completed...19.6
>>> sec
>>> Simulate year 1990:
>>> completed...................................26.4 sec
>>> Closing log file: C://urbansim_cache/
>>> chittco_1990_baseyear_cache\year_1990_log.txt
>>> Starting simulation for year 1990:
>>> completed........................26.4 sec
>>> Start simulation run:
>>> completed.........................................26.4 sec
>>> Closing log file: C://urbansim_cache/chittco_1990_baseyear_cache
>>> \run_multiprocess.log_______________________________________________
>>> Users mailing list
>>> Users_at_urbansim.org
>>> http://www.urbansim.org/mailman/listinfo/users
>>>
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>>
Received on Wed Mar 05 2008 - 21:31:14 PST
This archive was generated by hypermail 2.2.0 : Wed Mar 05 2008 - 21:31:15 PST