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Multinomiaalinen logistinen regressio×Sisäkkäinen logit-valintamalli×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19741985
KehittäjäMcFaddenDaniel McFadden; Ben-Akiva & Lerman
TyyppiMultinomial logistic regressionDiscrete choice regression model
AlkuperäislähdeMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Ben-Akiva, M., & Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press. ISBN: 978-0-262-02217-0
Rinnakkaisnimetmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik RegresyonTree Logit Model, Hierarchical Logit Model, Generalized Extreme Value Logit, İç İçe Logit Modeli
Liittyvät53
TiivistelmäMultinomial 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.The Nested Logit model is a discrete choice framework that groups mutually exclusive alternatives into hierarchical nests, allowing correlated unobserved utilities within each nest while maintaining independence across nests. Introduced formally by Ben-Akiva and Lerman (1985) and grounded in McFadden's Generalized Extreme Value (GEV) theory, it extends the standard Multinomial Logit by relaxing the restrictive Independence of Irrelevant Alternatives assumption within predefined groups of similar alternatives.
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ScholarGateVertaile menetelmiä: Multinomial Logit · Nested Logit. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare