Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Устойчива отрицателна биномна регресия× | Модел с нулево надуване× | |
|---|---|---|
| Област | Статистика | Статистика |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000s–2011 | 1992 |
| Създател≠ | Hilbe, J. M.; Zeileis, A. et al. | Diane Lambert |
| Тип≠ | Count regression with robust inference | Count regression with excess zeros |
| Основополагащ източник≠ | Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. ISBN: 978-0521198158 | Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗ |
| Други названия | robust NB regression, negative binomial regression with robust standard errors, sandwich-corrected negative binomial regression, NB2 robust regression | ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial |
| Свързани | 6 | 6 |
| Резюме≠ | Robust Negative Binomial Regression models overdispersed count outcomes using the negative binomial distribution while protecting coefficient inference against misspecification of the variance function. It pairs maximum-likelihood estimation of the mean and dispersion parameters with sandwich (Huber-White) standard errors, yielding valid tests even when the assumed variance structure is only approximately correct. | 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. |
| ScholarGateНабор от данни ↗ |
|
|