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| Bayesiansk MA-modell (Moving Average)× | Bayesiansk ARMA-modell× | |
|---|---|---|
| Ämnesområde | Ekonometri | Ekonometri |
| Familj | Regression model | Regression model |
| Ursprungsår≠ | 1970s–1997 | 1970s–1980s |
| Upphovsperson≠ | Bayesian framework applied to Box-Jenkins MA models; West & Harrison (1997) canonical treatment | Box & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s |
| Typ | Bayesian time series model | Bayesian time series model |
| Ursprungskälla≠ | West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259 | Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. link ↗ |
| Alias | Bayesian MA, Bayesian moving average, BMA time series, MA model with Bayesian estimation | Bayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference |
| Närliggande | 6 | 6 |
| Sammanfattning≠ | The 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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