So sánh phương pháp

	Mô hình Tuyến tính Tổng quát (GLM)	Hồi quy Poisson và Âm nhị thức
Lĩnh vực	Thống kê	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1972	1998
Người khởi xướng	John A. Nelder & Robert W. M. Wedderburn	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Loại	Regression framework	Generalized linear model for count data
Công trình gốc	Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Tên gọi khác	GLM, generalized regression, exponential family regression, link-function model	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Liên quan	6	4
Tóm tắt	The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.	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.