An Empirical Bayes Procedure for Improving Individual-Level Estimates and Predictions From Finite Mixtures of Multinomial Logit Models
改善多项Logit有限混合模型个体估计与预测的经验贝叶斯方法
with by specifying either a multinomial or a normal distribution of the coefficients, leading to finite mixture logit and mixed logit models. Focusing on the former, we show that individual-level estimates and predictions of finite mixtures estimated by maximizing the likelihood function can be improved through integration over the estimation error of the hyperparameters, using an empirical Bayes approach. We investigate the conjecture that this approach is more robust…