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Model zerowany z nadmierną liczbą zer (Robust Zero-Inflated Model)×Odporny uogólniony model liniowy×
DziedzinaStatystykaStatystyka
RodzinaRegression modelRegression model
Rok powstania1990s–2000s2001
TwórcaExtension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errorsCantoni & Ronchetti
TypRobust count regression with excess zerosRobust regression model
Źródło pierwotneZeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25. DOI ↗Heritier, S., Cantoni, E., Copt, S., & Victoria-Feser, M.-P. (2009). Robust Methods in Biostatistics. Wiley. ISBN: 978-0470027264
Inne nazwyrobust ZIP, robust ZINB, outlier-resistant zero-inflated regression, robust zero-inflated Poissonrobust GLM, GLM with robust estimation, robust quasi-likelihood model, M-estimator GLM
Pokrewne55
PodsumowanieThe 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.
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

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