Time series modeling, computation, and inference
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It...
| Otros Autores: | , |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
Chapman and Hall/CRC, an imprint of Taylor and Francis
[2010].
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| Edición: | 1st edition |
| Colección: | Texts in statistical science.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629708106719 |
Tabla de Contenidos:
- Front cover; Contents; Preface; Chapter 1: Notation, definitions, and basic inference; Chapter 2: Traditional time domain models; Chapter 3: The frequency domain; Chapter 4: Dynamic linear models; Chapter 5: State-space TVAR models; Chapter 6: General state-space models andsequential Monte Carlo methods; Chapter 7: Mixture models in time series; Chapter 8: Topics and examples in multipletime series; Chapter 9: Vector AR and ARMA models; Chapter 10: Multivariate DLMs and covariance models; Bibliography; Author Index; Subject Index; Back cover
