Skip to contents

Example data

debiasR_example_data()
Load empirical travel-to-work example data
simulated_active.users
Simulated Active User Counts by Origin
simulated_benchmark.od
Simulated Benchmark Origin-Destination Flows
simulated_covariates
Simulated Area Covariates
simulated_coverage
Simulated Coverage Inputs
simulated_distance
Simulated OD Distance Matrix
simulated_mpd.od
Simulated MPD Origin-Destination Flows
simulated_pop
Simulated Benchmark Population by Origin

Measure bias

measure_bias()
Measure Coverage Bias
measure_bias_distribution()
Measure active-user versus population distribution bias
validate_bias_residual_structure()
Validate Bias Residual Structure

Adjust flows

adjust_coefficient()
Global coefficient calibration with multiple model families
adjust_inverse_penetration()
Inverse penetration rate weights
adjust_multilevel_bayes()
Bayesian Multilevel Bias Adjustment for OD Flows (v0.2 Stage 1)
adjust_raking_ratio()
Raking ratio / IPF adjustment of OD flows
adjust_selection_rate()
Selection-rate weighting (Chi et al. with r_t calibration)
adjust_selection_rate2()
Selection Rate II weighting (Zagheni & Weber 2012) with k calibration

Validate flows

validate_flow_distribution()
Validate origin-conditioned destination-share distributions
validate_flow_overall() validate_flow_benchmark()
Validate adjusted OD flows against a benchmark overall
validate_flow_pairs() validate_flow_all()
Build an OD-pair validation table for MPD, adjusted, and benchmark flows
validate_flow_residual_structure()
Validate residual structure and randomness diagnostics
validate_flow_residuals()
Build richer OD-level residual diagnostics for adjusted versus benchmark flows