পদ্ধতির তুলনা করুন

	Robust Zero-Inflated Model	Robust Generalized Linear Model
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1990s–2000s	2001
প্রবর্তক	Extension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errors	Cantoni & Ronchetti
ধরন	Robust count regression with excess zeros	Robust regression model
মৌলিক উৎস	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
অপর নাম	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
সম্পর্কিত	5	5
সারসংক্ষেপ	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.