So sánh phương pháp

	Mô hình lạm phát số không	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 with excess zeros	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 model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Liên quan	6	4
Tóm tắt	A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.	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.