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Multinomisk logistisk regression×Poisson- og negativ binomialregression×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår19741998
OphavspersonMcFaddenCameron & Trivedi (textbook treatment); Hilbe (negative binomial)
TypeMultinomial logistic regressionGeneralized linear model for count data
Oprindelig kildeMcFadden, 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 ↗
Aliassermultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyoncount regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Relaterede54
ResuméMultinomial 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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ScholarGateSammenlign metoder: Multinomial Logit · Poisson Regression. Hentet 2026-06-15 fra https://scholargate.app/da/compare