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Robustný model s nadbytkom núl×Robustná regresia s negatívnym binomickým rozdelením×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku1990s–2000s2000s–2011
TvorcaExtension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errorsHilbe, J. M.; Zeileis, A. et al.
TypRobust count regression with excess zerosCount regression with robust inference
Pôvodný zdrojZeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25. DOI ↗Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press. ISBN: 978-0521198158
Ďalšie názvyrobust ZIP, robust ZINB, outlier-resistant zero-inflated regression, robust zero-inflated Poissonrobust NB regression, negative binomial regression with robust standard errors, sandwich-corrected negative binomial regression, NB2 robust regression
Príbuzné56
ZhrnutieThe robust zero-inflated model extends standard zero-inflated count regression — which handles excess zeros via a mixture of a point mass at zero and a count distribution — by replacing or supplementing classical maximum likelihood with robust estimation techniques (M-estimators, sandwich standard errors) that protect against the distorting influence of outlying observations.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.
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ScholarGatePorovnať metódy: Robust Zero-Inflated Model · Robust Negative Binomial Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare