השוואת שיטות

	מודל רובסטי עם אינפלציית אפסים	מודל לינארי מוכלל חסין
תחום	סטטיסטיקה	סטטיסטיקה
משפחה	Regression model	Regression model
שנת המקור	1990s–2000s	2001
הוגה השיטה	Extension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errors	Cantoni & Ronchetti
סוג	Robust count regression with excess zeros	Robust regression model
מקור מכונן	Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25.	Heritier, S., Cantoni, E., Copt, S., & Victoria-Feser, M.-P. (2009). Robust Methods in Biostatistics. Wiley. ISBN: 978-0470027264
כינויים	robust ZIP, robust ZINB, outlier-resistant zero-inflated regression, robust zero-inflated Poisson	robust GLM, GLM with robust estimation, robust quasi-likelihood model, M-estimator GLM
קשורות	5	5
תקציר	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.	A Robust Generalized Linear Model fits the standard GLM family — linear, logistic, Poisson, and others — using M-type estimating equations that down-weight outlying or influential observations. The result is coefficient estimates and standard errors that remain stable even when a minority of data points deviate sharply from the assumed distribution.