A Latent Variable Representation of Count Data Models to Accommodate Spatial and Temporal Dependence : Application to Predicting Crash Frequency at Intersections

@inproceedings{Castro2011ALV,
  title={A Latent Variable Representation of Count Data Models to Accommodate Spatial and Temporal Dependence : Application to Predicting Crash Frequency at Intersections},
  author={Marisol Castro and Rajesh Paleti and Chandra R. Bhat},
  year={2011}
}
This paper proposes a reformulation of count models as a special case of generalized orderedresponse models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in… CONTINUE READING

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