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분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도19742011
창시자McFaddenHilbe (textbook treatment); generalized linear model framework
유형Multinomial logistic regressionGeneralized linear model for count data
원전McFadden, 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 ↗
별칭multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik RegresyonNB regression, NB2 regression, negatif binom regresyonu
관련54
요약Multinomial 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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ScholarGate방법 비교: Multinomial Logit · Negative Binomial Regression. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare