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Модели пространственного взаимодействия (гравитационные модели)×Мультиномиальная логистическая регрессия×
ОбластьПространственный анализЭконометрика
СемействоRegression modelRegression model
Год появления19711974
Автор методаAlan Wilson (entropy-maximizing family)McFadden
ТипModel of flows between spatial origins and destinationsMultinomial logistic regression
Основополагающий источникWilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
Другие названияgravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modelimultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Связанные45
СводкаSpatial 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.Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category.
ScholarGateНабор данных
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ScholarGateСравнение методов: Spatial Interaction Model · Multinomial Logit. Получено 2026-06-15 из https://scholargate.app/ru/compare