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| ベイジアンARMAモデル× | ARMAモデル(自己回帰移動平均)× | |
|---|---|---|
| 分野 | 計量経済学 | 計量経済学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1970s–1980s | 1970 |
| 提唱者≠ | Box & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s | George E. P. Box and Gwilym M. Jenkins |
| 種類≠ | Bayesian time series model | Time series model |
| 原典≠ | Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. link ↗ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| 別名 | Bayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) |
| 関連≠ | 6 | 5 |
| 概要≠ | 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. | The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting. |
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