Flexible Covariance Structures for Categorical Dependent Variables Through Finite Mixtures of Generalized Extreme Value Models
分类因变量的灵活协方差结构：广义极值模型的有限混合
miks), is introduced. These arise from the combination of a finite number of core Generalized Extreme Value (GEV) models to achieve more flexible functional forms, particularly in terms of error covariance structures. Example members of the class include combinations of (1) Multinomial Logit (MNL) models with differing scales, (2) multinomial logit with nested MNL models, (3) tree extreme value models with differing preference trees, and so on. Compatibility of FinMix models…