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| Zero-Inflated Model× | 과잉 제로를 갖는 계수 데이터에 대한 허들 모형× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1992 | 1986 |
| 창시자≠ | Diane Lambert | Mullahy |
| 유형≠ | Count regression with excess zeros | Two-part count model |
| 원전≠ | Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗ | Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365. DOI ↗ |
| 별칭 | ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial | hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model) |
| 관련≠ | 6 | 5 |
| 요약≠ | A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts. | 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. |
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