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Bayesiläinen liukuvan keskiarvon (MA) malli×Bayesiläinen ARMA-malli×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi1970s–19971970s–1980s
KehittäjäBayesian framework applied to Box-Jenkins MA models; West & Harrison (1997) canonical treatmentBox & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s
TyyppiBayesian time series modelBayesian time series model
AlkuperäislähdeWest, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. link ↗
RinnakkaisnimetBayesian MA, Bayesian moving average, BMA time series, MA model with Bayesian estimationBayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference
Liittyvät66
TiivistelmäThe Bayesian MA model estimates a moving average time series model within a fully Bayesian framework, placing prior distributions on the MA parameters and error variance and updating them via Bayes' theorem. This approach yields full posterior distributions over model parameters and produces probabilistic forecasts with coherent uncertainty quantification.The Bayesian ARMA model applies Bayesian inference to the classical autoregressive moving average framework for stationary univariate time series. Rather than producing single point estimates for the AR and MA parameters, it yields full posterior distributions, naturally incorporating prior knowledge and providing coherent uncertainty quantification over forecasts and impulse responses.
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ScholarGateVertaile menetelmiä: Bayesian MA model · Bayesian ARMA model. Haettu 2026-06-15 osoitteesta https://scholargate.app/fi/compare