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 |
|---|---|
| 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