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Bayesovský model náhodných efektů×Model náhodných efektů pro panelová data×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku1972–19952021
TvůrceLindley & Smith (1972); extended by Gelman, Rubin and colleaguesBaltagi (textbook treatment); classical random-effects panel estimator
TypBayesian hierarchical panel modelPanel data regression
Původní zdrojGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. DOI ↗
Další názvyBayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREMrandom effects panel model, RE estimator, GLS random effects, Panel Veri — Rassal Etkiler Modeli
Příbuzné55
ShrnutíThe Bayesian random effects model combines panel-data random effects with a Bayesian prior framework, allowing unit-specific effects to be treated as draws from a population distribution whose hyperparameters are estimated from the data. This produces regularised, uncertainty-quantified estimates that borrow strength across units — particularly valuable for short panels, sparse groups, or settings where frequentist variance-component estimation is unstable.The Random Effects model is a panel-data regression that treats unobserved individual heterogeneity as a random component drawn from a common distribution, rather than a separate parameter for each unit. It is a standard estimator in panel econometrics, developed in textbook treatments such as Baltagi's Econometric Analysis of Panel Data (2021).
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ScholarGatePorovnat metody: Bayesian Random Effects Model · Random Effects Model. Získáno 2026-06-15 z https://scholargate.app/cs/compare