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CHAPTERS
- Notation, definitions and basic inference
- Traditional linear time series models
- The frequency domain
- Dynamic linear models
- State-space TVAR models
- General state-space models
- Mixture models in time series
- Topics and examples in multiple time series
- Vector AR and ARMA models
- General classes of multivariate dynamic models
- Latent factor models
This is the 2021 updated and extended version of the 2010 1st edition (Prado & West)
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