So sánh phương pháp

	Hồi quy Quantile	Hồi quy Poisson và Âm nhị thức
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1978	1998
Người khởi xướng	Koenker & Bassett	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Loại	Conditional quantile regression	Generalized linear model for count data
Công trình gốc	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Tên gọi khác	conditional quantile regression, regression quantiles, Kantil Regresyon	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Liên quan	5	4
Tóm tắt	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.	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.