পদ্ধতির তুলনা করুন

	মিশ্র লজিট মডেল	স্থানিক মিথস্ক্রিয়া (মহাকর্ষ) মডেল
ক্ষেত্র	অর্থমিতি	স্থানিক বিশ্লেষণ
পরিবার	Regression model	Regression model
উদ্ভবের বছর	2000	1971
প্রবর্তক	Daniel McFadden & Kenneth Train	Alan Wilson (entropy-maximizing family)
ধরন	Random-parameters discrete choice model	Model of flows between spatial origins and destinations
মৌলিক উৎস	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.
অপর নাম	Random Parameters Logit, Mixed Multinomial Logit, Error Components Logit, Karma Logit Modeli	gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
সম্পর্কিত	3	4
সারসংক্ষেপ	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.