Authors: Durbin J., Koopman S.J.
Year:2012 Pages:369 Language:English Size:2 Mb Extension:pdf
- Time Series Analysis by State Space Methods [2 ed.](2012).pdf
Contents
1. Introduction
PART I THE LINEAR STATE SPACE MODEL
2. Local level model
3. Linear state space models
4. Filtering, smoothing and forecasting
5. Initialisation of filter and smoother
6. Further computational aspects
7. Maximum likelihood estimation of parameters
8. Illustrations of the use of the linear model
PART II NON-GAUSSIAN AND NONLINEAR STATE SPACE MODELS
9. Special cases of nonlinear and non-Gaussian models
10. Approximate filtering and smoothing
11. Importance sampling for smoothing
12. Particle filtering
13. Bayesian estimation of parameters
14. Non-Gaussian and nonlinear illustrations