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ロバストゼロ過剰モデル×ロバスト負の二項回帰×
分野統計学統計学
系統Regression modelRegression model
提唱年1990s–2000s2000s–2011
提唱者Extension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errorsHilbe, J. M.; Zeileis, A. et al.
種類Robust count regression with excess zerosCount regression with robust inference
原典Zeileis, 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
別名robust 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
関連56
概要The 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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ScholarGate手法を比較: Robust Zero-Inflated Model · Robust Negative Binomial Regression. 2026-06-17に以下より取得 https://scholargate.app/ja/compare