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Bayesian Weighted Least Squares (Bayesian WLS)×Bayesian random effects model×
ValdkondÖkonomeetriaÖkonomeetria
PerekondRegression modelRegression model
Tekkeaasta19711972–1995
LoojaArnold Zellner (Bayesian econometrics framework)Lindley & Smith (1972); extended by Gelman, Rubin and colleagues
TüüpBayesian weighted regressionBayesian hierarchical panel model
AlgallikasZellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley, New York. ISBN: 978-0471169376Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
RööpnimetusedBayesian weighted regression, BWLS, Bayesian heteroscedastic regression, weighted Bayesian linear regressionBayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREM
Seotud45
KokkuvõteBayesian Weighted Least Squares combines the classical WLS weighting scheme — which downweights observations with high error variance — with Bayesian prior distributions over the regression coefficients and error variance. The result is a posterior distribution that reflects both the data likelihood and prior beliefs, providing full uncertainty quantification in heteroscedastic settings.The 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.
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ScholarGateVõrdle meetodeid: Bayesian WLS · Bayesian Random Effects Model. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare