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Modèle autorégressif (AR) bayésien×Autoregressive Vectoriel (VAR)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine19711980
Auteur d'origineArnold Zellner; foundational Bayesian time-series work by West & HarrisonChristopher A. Sims
TypeBayesian time-series modelMultivariate time-series model
Source fondatriceZellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
AliasBayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregressionVAR, VAR model, vector autoregressive model, multivariate autoregression
Apparentées65
RésuméThe Bayesian AR model estimates an autoregressive time-series process by combining a likelihood derived from the AR structure with prior distributions over the lag coefficients and error variance. Rather than producing single point estimates, it yields full posterior distributions, enabling principled uncertainty quantification and probabilistic forecasting.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
ScholarGateJeu de données
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  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Bayesian AR model · Vector Autoregression. Consulté le 2026-06-15 sur https://scholargate.app/fr/compare