Abstract
The application of the continuous state space model to unequally spaced sequence data is discussed and illustrated. The continuous model implies a discrete model for the observed data. Practical expressions for relevant discrete model quantities are given. These quantites are required for the digital processing of the data and in particular for the application of the Kalman and smoothing filter and related calculations. Applications illustrate the procedures.
| Original language | English |
|---|---|
| Pages (from-to) | 53-71 |
| Number of pages | 19 |
| Journal | Statistical Inference for Stochastic Processes |
| Volume | 4 |
| Publication status | Published - 2001 |
Keywords
- Kalman filter
- splines
- smoothing
- state space model
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Cite this
De Jong, P., & Mazzi, S. (2001). Modeling and smoothing unequally spaced sequence data. Statistical Inference for Stochastic Processes, 4, 53-71.