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Logistička regresija s više kategorija×Poissonova i negativna binomna regresija×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19741998
TvoracMcFaddenCameron & Trivedi (textbook treatment); Hilbe (negative binomial)
VrstaMultinomial logistic regressionGeneralized linear model for count data
Temeljni izvorMcFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗
Drugi nazivimultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyoncount regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Srodne54
SažetakMultinomial 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.Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.
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ScholarGateUsporedite metode: Multinomial Logit · Poisson Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare