Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель бар'єру для даних підрахунку× | Пуассонівська та від’ємна біноміальна регресія× | |
|---|---|---|
| Галузь≠ | Статистика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1986 | 1998 |
| Автор методу≠ | Mullahy | Cameron & Trivedi (textbook treatment); Hilbe (negative binomial) |
| Тип≠ | Two-part count model | Generalized linear model for count data |
| Основоположне джерело≠ | Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365. DOI ↗ | Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗ |
| Інші назви | 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 |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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