Data-Driven Models
Data-Driven Models
Empirical forecasting models · Sources
Primary papers, model variants, source notes, and review signals behind the Kalman filter page.
Reference material used for orientation; read primary and academic sources first when claims conflict.
[S1] Reference
Kalman (1960) derived the optimal linear recursive filter for Gaussian state-space models.
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[S2] Reference
Rauch, Tung, and Striebel (1965) developed the fixed-interval smoother (backward pass after the forward filter).
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[S3] Reference
Harvey (1989) brought the Kalman filter into mainstream econometrics, showing how UCMs, ARIMA, and structural time-series models all fit the state-space framework.
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[S4] Reference
Hamilton (1994, Chapter 13) provided a textbook treatment connecting the Kalman filter to time-series econometrics.
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[S5] Reference
Durbin and Koopman (2012) gave a comprehensive treatment of state-space methods including diffuse initialization, missing data, and simulation smoothing.
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[S6] Reference
Anderson and Moore (1979) established the control-theoretic foundations: observability, controllability, and filter convergence.
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[S7] Reference
De Jong (1991) developed the diffuse Kalman filter for non-stationary initial conditions.
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