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领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份19742011
提出者McFaddenHilbe (textbook treatment); generalized linear model framework
类型Multinomial logistic regressionGeneralized linear model for count data
开创性文献McFadden, 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 ↗
别名multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik RegresyonNB regression, NB2 regression, negatif binom regresyonu
相关54
摘要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.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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ScholarGate方法对比: Multinomial Logit · Negative Binomial Regression. 于 2026-06-15 检索自 https://scholargate.app/zh/compare