Doubly generalized logit: A closed-form discrete choice model system with multivariate generalized extreme value distributed utilities
Doubly generalized logit: A closed-form discrete choice model system with multivariate generalized extreme value distributed utilities
复制标题
双广义logit：具有多元广义极值分布式效用的闭式离散选择模型系统
DOI：
10.1016/j.trc.2021.103315
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Chikaraishi Makoto
中科院分区：
文献类型：
--
作者：
Nakayama Shoichiro;Chikaraishi Makoto
在这项研究中，我们推广了我们以前的q-广义多项Logit模型(Nakayama&Chikaraishi，2015)，其中考虑了效用分布的异方差和灵活形状，允许备选方案的统计相关性。这是通过引入麦克法登多元Gumbel分布的q-推广来实现的。因此，Logit模型是双重推广的；1)每个效用服从广义极值分布，其中包括Gumbel分布、威布尔分布和弗雷谢特分布；以及2)效用分布是多元的，因此，允许备选方案的嵌套或交叉嵌套结构和依赖。所提出的双重广义Logit模型系统允许导出新的闭式离散选择模型，如q-广义嵌套Logit模型和q-广义交叉嵌套Logit(CNL)模型。此外，该模型系统包括传统的Logit模型，如多项Logit、嵌套Logit和CNL模型作为特例，以及新的广义Logit模型，同时保留了闭合形式的表达式。我们的经验证实，在某些情况下，所提出的模型的拟合度可以比传统模型好得多，尽管改进的程度因情况而异。
In this study, we generalize our previousq-generalized multinomial logit model (Nakayama & Chikaraishi, 2015), in which the heteroscedastic variance and flexible shape of the utility distribution are considered, by allowing for statistical dependency of alternatives. This is achieved by introducing theq-generalization of McFadden’s multivariate Gumbel distribution. Thus, the logit model is doubly generalized; 1) each utility follows the generalized extreme value distribution that includes the Gumbel, Weibull, and Fréchet distributions; and 2) the utility distribution is multivariate, and therefore, a nested or cross-nested structure and dependency of alternatives are allowed. The proposed doubly generalized logit model system allows for deriving new closed-form discrete choice models such as theq-generalized nested logit model andq-generalized cross-nested logit (CNL) model. Furthermore, the model system includes conventional logit models such as the multinomial logit, nested logit, and CNL models as special cases as well as the new generalized logit models, while retaining a closed-form expression. We empirically confirm that the goodness-of-fit of the proposed model could be substantially better compared to that of the conventional models in some cases, though the degree of improvements varies across cases.
交叉嵌套 Logit 模型协方差的实用易处理表达式
影响因子：
6.8
作者：
V. Marzano;A. Papola;F. Simonelli;R. Vitillo
通讯作者：
R. Vitillo