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Model mešovitog logita×Modeli prostorne interakcije (gravitacioni modeli)×
OblastEkonometrijaProstorna analiza
PorodicaRegression modelRegression model
Godina nastanka20001971
TvoracDaniel McFadden & Kenneth TrainAlan Wilson (entropy-maximizing family)
TipRandom-parameters discrete choice modelModel of flows between spatial origins and destinations
Temeljni izvorTrain, K. E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. ISBN: 978-0-521-74738-7Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗
Drugi naziviRandom Parameters Logit, Mixed Multinomial Logit, Error Components Logit, Karma Logit Modeligravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Srodne34
SažetakThe Mixed Logit model, introduced formally by McFadden and Train (2000) and elaborated in Train (2009), is a flexible discrete choice framework that allows preference parameters to vary randomly across decision-makers. By integrating standard logit probabilities over a mixing distribution of coefficients, it overcomes the restrictive independence of irrelevant alternatives (IIA) property and accommodates unobserved taste heterogeneity, panel data correlation, and complex substitution patterns across 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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ScholarGateUporedite metode: Mixed Logit · Spatial Interaction Model. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare