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Geschachteltes Logit-Modell für diskrete Wahlentscheidungen×Multinomiale Logistische Regression×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr19851974
UrheberDaniel McFadden; Ben-Akiva & LermanMcFadden
TypDiscrete choice regression modelMultinomial logistic regression
Wegweisende QuelleBen-Akiva, M., & Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press. ISBN: 978-0-262-02217-0McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
AliasnamenTree Logit Model, Hierarchical Logit Model, Generalized Extreme Value Logit, İç İçe Logit Modelimultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Verwandt35
ZusammenfassungThe 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.Multinomial 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.
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ScholarGateMethoden vergleichen: Nested Logit · Multinomial Logit. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare