Сравнение методов

	Модель барьера для счетных данных	Пуассоновская регрессия и регрессия с отрицательным биномиальным распределением
Область	Статистика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1986	1998
Автор метода	Mullahy	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Тип	Two-part count model	Generalized linear model for count data
Основополагающий источник	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.
Другие названия	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
Связанные	5	4
Сводка	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.