方法证据记录
State Space Model
A state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.
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。
State Space Model (Kalman Filter)
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. · DOI 10.1017/CBO9781107049994
- Durbin, J. & Koopman, S. J. (2012). Time Series Analysis by State Space Methods (2nd ed.). Oxford University Press. · DOI 10.1093/acprof:oso/9780199641178.001.0001
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