Regression modelEconometrics / time series
贝叶斯 ARIMA 模型
贝叶斯 ARIMA 模型将经典的 Box-Jenkins ARIMA 框架与贝叶斯推断相结合。它不为自回归和移动平均参数获取单点估计值，而是为它们设置先验分布，并利用观测数据将信念更新为完整的后验分布，从而实现连贯的不确定性量化和概率预测。
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来源
- Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903
- Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
如何引用本页
ScholarGate. (2026, June 3). Bayesian Autoregressive Integrated Moving Average Model. ScholarGate. https://scholargate.app/zh/econometrics/bayesian-arima-model
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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