방법 비교

	과잉 제로를 갖는 계수 데이터에 대한 허들 모형	포아송 및 음이항 회귀분석
분야	통계학	계량경제학
계열	Regression model	Regression model
기원 연도	1986	1998
창시자	Mullahy	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
유형	Two-part count model	Generalized linear model for count data
원전	Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
별칭	hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model)	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
관련	5	4
요약	The hurdle model is a two-part count-data model introduced by Mullahy (1986). A first stage models the binary choice of crossing a hurdle (a zero versus a non-zero count), and a second stage models the strictly positive counts with a zero-truncated distribution such as a zero-truncated Poisson or negative binomial.	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.