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Bayesov probit model×Probit regresijski model×
PodručjeStatistikaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19932018
TvoracAlbert & Chib (data augmentation formulation)Greene (textbook treatment); classical discrete-choice modelling
VrstaBinary regression (Bayesian)Binary discrete-choice model
Temeljni izvorAlbert, J. H., & Chib, S. (1993). Bayesian analysis of binary and polychotomous response data. Journal of the American Statistical Association, 88(422), 669-679. DOI ↗Greene, W. H. (2018). Econometric Analysis (8th ed.). Pearson. ISBN: 978-0134461366
Drugi naziviBayesian probit regression, probit model with data augmentation, Gibbs sampling probit, Albert-Chib probitprobit regression, normit model, Probit Modeli
Srodne65
SažetakThe Bayesian Probit model is a binary regression method that models the probability of a binary outcome using the normal CDF (probit link) within a Bayesian framework. It assigns prior distributions to regression coefficients and updates them with observed data, yielding a full posterior distribution rather than a single point estimate. The Albert-Chib data-augmentation algorithm makes posterior sampling computationally efficient via Gibbs sampling.The probit model is a regression method for a binary (0/1) outcome that maps a linear index of the predictors through the standard normal cumulative distribution function to produce a probability. It is a classical discrete-choice alternative to logistic regression, developed in standard econometrics treatments such as Greene's Econometric Analysis (2018).
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ScholarGateUsporedite metode: Bayesian Probit model · Probit Model. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare