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Multinomiale Logistische Regression×Negative Binomial Regression×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr19742011
UrheberMcFaddenHilbe (textbook treatment); generalized linear model framework
TypMultinomial logistic regressionGeneralized linear model for count data
Wegweisende QuelleMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. DOI ↗
Aliasnamenmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik RegresyonNB regression, NB2 regression, negatif binom regresyonu
Verwandt54
ZusammenfassungMultinomial 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.Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.
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ScholarGateMethoden vergleichen: Multinomial Logit · Negative Binomial Regression. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare