השוואת שיטות

	מודל מנופח-אפס (Zero-Inflated Model)	רגרסיית בינום שלילי
תחום	סטטיסטיקה	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	1992	2011
הוגה השיטה	Diane Lambert	Hilbe (textbook treatment); generalized linear model framework
סוג	Count regression with excess zeros	Generalized linear model for count data
מקור מכונן	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.
כינויים	ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial	NB regression, NB2 regression, negatif binom regresyonu
קשורות	6	4
תקציר	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.