เปรียบเทียบวิธี

	แบบจำลองโลจิตแบบผสม	แบบจำลองอันตรกิริยาเชิงพื้นที่ (แบบจำลองแรงโน้มถ่วง)
สาขาวิชา	เศรษฐมิติ	การวิเคราะห์เชิงพื้นที่
ตระกูล	Regression model	Regression model
ปีกำเนิด	2000	1971
ผู้ริเริ่ม	Daniel McFadden & Kenneth Train	Alan Wilson (entropy-maximizing family)
ประเภท	Random-parameters discrete choice model	Model of flows between spatial origins and destinations
แหล่งต้นตำรับ	Train, K. E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. ISBN: 978-0-521-74738-7	Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32.
ชื่อเรียกอื่น	Random Parameters Logit, Mixed Multinomial Logit, Error Components Logit, Karma Logit Modeli	gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
ที่เกี่ยวข้อง	3	4
สรุป	The 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.