方法对比
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| 嵌套 Logit 离散选择模型× | 空间交互（引力）模型× | |
|---|---|---|
| 领域≠ | 计量经济学 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1985 | 1971 |
| 提出者≠ | Daniel McFadden; Ben-Akiva & Lerman | Alan Wilson (entropy-maximizing family) |
| 类型≠ | Discrete choice regression model | Model of flows between spatial origins and destinations |
| 开创性文献≠ | Ben-Akiva, M., & Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press. ISBN: 978-0-262-02217-0 | Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗ |
| 别名 | Tree Logit Model, Hierarchical Logit Model, Generalized Extreme Value Logit, İç İçe Logit Modeli | gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli |
| 相关≠ | 3 | 4 |
| 摘要≠ | The Nested Logit model is a discrete choice framework that groups mutually exclusive alternatives into hierarchical nests, allowing correlated unobserved utilities within each nest while maintaining independence across nests. Introduced formally by Ben-Akiva and Lerman (1985) and grounded in McFadden's Generalized Extreme Value (GEV) theory, it extends the standard Multinomial Logit by relaxing the restrictive Independence of Irrelevant Alternatives assumption within predefined groups of similar alternatives. | Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis. |
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