So sánh phương pháp

	Hồi quy Poisson có lạm phát số không (ZIP)	Hồi quy Poisson và Âm nhị thức
Lĩnh vực	Thống kê	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1992	1998
Người khởi xướng	Diane Lambert	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Loại	Count regression (two-component mixture)	Generalized linear model for count data
Công trình gốc	Lambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Tên gọi khác	ZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Liên quan	4	4
Tóm tắt	Zero-Inflated Poisson regression is a two-component model for count data that contains more zeros than an ordinary Poisson model can explain. Introduced by Diane Lambert in 1992, it combines a logistic model for the zero-generating mechanism with a Poisson model for the genuine counting process.	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.