方法证据记录
Time-varying parameter SARIMA model
The Time-Varying Parameter SARIMA model extends the classical SARIMA framework by allowing autoregressive and moving-average coefficients to evolve over time. Cast as a state-space system and estimated with the Kalman filter, it captures both seasonal patterns and structural change within a single unified model.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Time-Varying Parameter Seasonal Autoregressive Integrated Moving Average Model
分类方法记录 · regression-model / econometrics
- Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. · ISBN 9780521321969
- Durbin, J., & Koopman, S. J. (2012). Time Series Analysis by State Space Methods (2nd ed.). Oxford University Press. · ISBN 9780199641178
精选声明
声明已持久化到证据分类账中，每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时，此视图不会自行创建声明评估。
相关方法
从方法图中生成，显示为机器建议的关系 — 不推断任何证据声明。