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| Hurdle-Modell für Zähldaten× | Poisson- und Negativ-Binomial-Regression× | |
|---|---|---|
| Fachgebiet≠ | Statistik | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1986 | 1998 |
| Urheber≠ | Mullahy | Cameron & Trivedi (textbook treatment); Hilbe (negative binomial) |
| Typ≠ | Two-part count model | Generalized linear model for count data |
| Wegweisende Quelle≠ | 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 ↗ |
| Aliasnamen | 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 |
| Verwandt≠ | 5 | 4 |
| Zusammenfassung≠ | 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. |
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