विधियों की तुलना करें

	शून्य-फुलाया ऋणात्मक द्विपद (ZINB) प्रतिगमन	शून्य-स्फीत पॉइसन (ZIP) प्रतिगमन
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1994	1992
प्रवर्तक	Greene (1994)	Diane Lambert
प्रकार	Count regression (mixture model)	Count regression (two-component mixture)
मौलिक स्रोत	Greene, W. H. (1994). Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models. NYU Working Paper.	Lambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14.
उपनाम	ZINB, ZINB regression, zero-inflated negative binomial model, Sıfır-Şişirilmiş Negatif Binom Regresyonu (ZINB)	ZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)
संबंधित	5	4
सारांश	Zero-Inflated Negative Binomial regression is a count model, introduced by Greene (1994), that handles count data showing both an excess of zeros and overdispersion. It combines a binary inflation process that generates structural zeros with a negative binomial count process, making it one of the most widely used distributions for real-world count data.	Zero-Inflated Poisson regression is a two-component model for count data that contains more zeros than an ordinary Poisson model can explain. Introduced by Diane Lambert in 1992, it combines a logistic model for the zero-generating mechanism with a Poisson model for the genuine counting process.