Closed-form Bayesian inferences for the logit model via polynomial expansions

@article{Miller2006ClosedformBI,
  title={Closed-form Bayesian inferences for the logit model via polynomial expansions},
  author={S. Miller and Eric T. Bradlow and Kevin D. Dayaratna},
  journal={Quantitative Marketing and Economics},
  year={2006},
  volume={4},
  pages={173-206}
}
Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary outcomes as studied here). However, the logit likelihood extended with a population distribution of heterogeneity doesn’t yield closed-form inferences, and therefore numerical integration techniques are relied upon (e.g., MCMC methods).We present here an alternative, closed-form Bayesian inferences for the logit model… Expand
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