방법 비교

	베이즈 토빗 모형	Zero-Inflated Model
분야	통계학	통계학
계열	Regression model	Regression model
기원 연도	1958 (classical); 1992 (Bayesian formulation)	1992
창시자	James Tobin (classical Tobit, 1958); Siddhartha Chib (Bayesian Tobit, 1992)	Diane Lambert
유형	Bayesian censored/limited-dependent-variable regression	Count regression with excess zeros
원전	Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24–36.	Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.
별칭	Bayesian censored regression, Bayesian Type I Tobit, Bayesian truncated regression, Tobit with priors	ZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial
관련	5	6
요약	The Bayesian Tobit model extends Tobin's censored regression framework by replacing maximum-likelihood point estimates with a full posterior distribution over regression coefficients and error variance. By embedding Gibbs sampling with data augmentation, it produces credible intervals, handles small censored samples gracefully, and naturally incorporates prior knowledge about effect sizes.	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.