পদ্ধতির তুলনা করুন

	Robust Zero-Inflated Model	শক্তিশালী পয়সন রিগ্রেশন
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1990s–2000s	2004
প্রবর্তক	Extension of Lambert (1992) ZIP model combined with robust M-estimation and sandwich standard errors	Guangyong Zou
ধরন	Robust count regression with excess zeros	GLM with robust variance
মৌলিক উৎস	Zeileis, A., Kleiber, C., & Jackman, S. (2008). Regression models for count data in R. Journal of Statistical Software, 27(8), 1–25.	Zou, G. (2004). A modified Poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702-706.
অপর নাম	robust ZIP, robust ZINB, outlier-resistant zero-inflated regression, robust zero-inflated Poisson	modified Poisson regression, Poisson regression with robust standard errors, log-binomial alternative, sandwich-variance Poisson
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.	Robust Poisson regression fits a Poisson log-linear model to a binary outcome but replaces the model-based variance with the empirical sandwich estimator. This yields valid standard errors and risk ratios even though Poisson variance assumptions are technically violated for binary data. The approach, popularized by Zou (2004), is widely used in epidemiology as a numerically stable alternative to log-binomial regression.