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Robust negativ binomialregression×Zero-inflaterad modell×
ÄmnesområdeStatistikStatistik
FamiljRegression modelRegression model
Ursprungsår2000s–20111992
UpphovspersonHilbe, J. M.; Zeileis, A. et al.Diane Lambert
TypCount regression with robust inferenceCount regression with excess zeros
UrsprungskällaHilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. ISBN: 978-0521198158Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗
Aliasrobust NB regression, negative binomial regression with robust standard errors, sandwich-corrected negative binomial regression, NB2 robust regressionZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial
Närliggande66
SammanfattningRobust 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.
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ScholarGateJämför metoder: Robust Negative Binomial Regression · Zero-inflated model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare