Abstract
A filter is presented which computes cross-validation errors and associated statistics for an arbitrary state space model. The procedure is more efficient than an existing approach. Diffuse initial conditions are easily handled using a minor extension. The relationship to the fixed interval smoothing algorithm is investigated.
Original language | English |
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Pages (from-to) | 594-600 |
Number of pages | 7 |
Journal | Biometrika |
Volume | 75 |
Issue number | 3 |
DOIs | |
Publication status | Published - Sep 1988 |
Externally published | Yes |
Keywords
- Cross-validation
- Diffuse initial conditions
- Kalman filter
- Smoothing filter