Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à seuil pour données de comptage× | Régression de Poisson à inflation de zéros (ZIP)× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1986 | 1992 |
| Auteur d'origine≠ | Mullahy | Diane Lambert |
| Type≠ | Two-part count model | Count regression (two-component mixture) |
| Source fondatrice≠ | Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365. DOI ↗ | Lambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14. DOI ↗ |
| Alias≠ | hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model) | ZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP) |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | 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. | Zero-Inflated Poisson regression is a two-component model for count data that contains more zeros than an ordinary Poisson model can explain. Introduced by Diane Lambert in 1992, it combines a logistic model for the zero-generating mechanism with a Poisson model for the genuine counting process. |
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