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Locpick: Modern location and destination choice modeling

Locpick: Modern location and destination choice modeling
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locpick is a Python library for estimating discrete choice models of location decisions — where individuals, households, or firms choose among spatially-defined alternatives (neighborhoods, jobs, housing units, transit stops). These methods have broad applicability but are common in regional land-use and housing market modeling. The package is designed for:

  • Large-scale urban models: 100K+ choosers, 1K+ alternatives
  • Sampling-based estimation: Most alternatives are irrelevant; only a sampled subset is evaluated per chooser
  • patial dependence: Nearby alternatives can affect each other or share unobserved attributes (via graph= on any model)
  • Heterogeneous preferences: Mixed logit for random taste variation
  • Nested structure: Nested logit for hierarchical choice (e.g., county → tract → block) J- AX-native computation: JIT-compiled kernels, GPU acceleration, automatic differentiation