Time series modeling, computation, and inference
Focusing on Bayesian approaches and computations using analytic and simulation-based methods for inference, Time Series: Modeling, Computation, and Inference, Second Edition integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications...
| Main Authors: | , |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL
CRC Press
2021
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| Edition: | Second edition |
| Series: | Texts in statistical science
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- 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