方法证据记录
Time Series Kalman Filter
The time series Kalman filter applies the Kalman filtering and smoothing algorithm within a state-space representation of time series models. It recursively extracts unobserved components — trend, seasonality, cycles, and irregular noise — from observed data, providing optimal filtered and smoothed state estimates together with their uncertainty, and enabling exact likelihood evaluation for parameter estimation.
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。
Kalman Filter for Time Series State-Space Models
分类方法记录 · bayesian / bayesian
- Durbin, J. & Koopman, S. J. (2012). Time Series Analysis by State Space Methods (2nd ed.). Oxford University Press. · ISBN 978-0199641178
- Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. · ISBN 978-0521321969
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