পদ্ধতির তুলনা করুন

	জিরো-ইনফ্লেটেড মডেল	নেগেটিভ বাইনোমিয়াল রিগ্রেশন
ক্ষেত্র	পরিসংখ্যান	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1992	2011
প্রবর্তক	Diane Lambert	Hilbe (textbook treatment); generalized linear model framework
ধরন	Count regression with excess zeros	Generalized linear model for count data
মৌলিক উৎস	Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.	Hilbe, J. M. (2011). Negative Binomial Regression (2nd ed.). Cambridge University Press.
অপর নাম	ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial	NB regression, NB2 regression, negatif binom regresyonu
সম্পর্কিত	6	4
সারসংক্ষেপ	A zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.	Negative Binomial Regression is a generalized linear model for count outcomes that extends Poisson regression to handle overdispersion, where the variance of the counts exceeds their mean. Developed in the GLM tradition and treated in depth by Hilbe (2011), it adds a dispersion parameter so that inference stays valid when Poisson would understate the spread of the data.