LIST OF CHAPTERS

1. Notation, definitions and basic inference
2. Traditional linear time series models
3. The frequency domain
4. Dynamic linear models
5. State-space TVAR models
6. General state-space models
7. Mixture models in time series
8. Topics and examples in multiple time series
9. Vector AR and ARMA models
10. Multivariate DLMs and covariance models