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رگرسیون لجستیک چندجمله‌ای (Multinomial Logistic Regression)×رگرسیون پواسون و دوجمله‌ای منفی×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش19741998
پدیدآورMcFaddenCameron & Trivedi (textbook treatment); Hilbe (negative binomial)
نوعMultinomial logistic regressionGeneralized linear model for count data
منبع بنیادینMcFadden, 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 ↗
نام‌های دیگرmultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyoncount regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
مرتبط54
خلاصهMultinomial 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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ScholarGateمقایسهٔ روش‌ها: Multinomial Logit · Poisson Regression. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare