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Régression logistique multinomiale×Modèles d'interaction spatiale (gravitationnelle)×
DomaineÉconométrieAnalyse spatiale
FamilleRegression modelRegression model
Année d'origine19741971
Auteur d'origineMcFaddenAlan Wilson (entropy-maximizing family)
TypeMultinomial logistic regressionModel of flows between spatial origins and destinations
Source fondatriceMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗
Aliasmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyongravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Apparentées54
RésuméMultinomial 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.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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ScholarGateComparer des méthodes: Multinomial Logit · Spatial Interaction Model. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare