1. Notation, definitions, and basic inference; 2. Traditional time domain models; 3. The frequency domain; 4. Dynamic linear models; 5. State-space TVAR models; 6. SMC methods for state-space models; 7. Mixture models in time series; 8. Topics and examples in multiple time series; 9. Vector AR and ARMA models; 10. General classes of multivariate dynamic models; 11. Latent factor models
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