56,50 €*
Versandkostenfrei per Post / DHL
Aktuell nicht verfügbar
This is the second edition of a popular graduate level textbook on time series modeling, computation and inference. The book is essentially unique in its approach, with a focus on Bayesian methods, although classical methods are also covered.
This is the second edition of a popular graduate level textbook on time series modeling, computation and inference. The book is essentially unique in its approach, with a focus on Bayesian methods, although classical methods are also covered.
Raquel Prado is Professor in the Department of Statistics at the Baskin School of Engineering of the University of California Santa Cruz, USA. Her main research areas are time series analysis and Bayesian modeling - with a focus on analysis of large-dimensional nonstationary time series data and applications to biomedical signal processing and brain imaging. Marco A. R. Ferreira is an Associate Professor in the Department of Statistics at Virginia Tech, where he served from 2016 to 2020 as the Director of Graduate Programs. Mike West holds a Duke University distinguished chair as the Arts & Sciences Professor of Statistics & Decision Sciences in the Department of Statistical Science, where he led the development of statistics from 1990-2002.
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
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Taschenbuch |
| Seiten: | 452 |
| ISBN-13: | 9781032040042 |
| ISBN-10: | 1032040041 |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Ferreira, Marco A. R.
West, Mike Prado, Raquel |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 156 x 235 x 28 mm |
| Von/Mit: | Marco A. R. Ferreira (u. a.) |
| Erscheinungsdatum: | 25.09.2023 |
| Gewicht: | 0,71 kg |
Raquel Prado is Professor in the Department of Statistics at the Baskin School of Engineering of the University of California Santa Cruz, USA. Her main research areas are time series analysis and Bayesian modeling - with a focus on analysis of large-dimensional nonstationary time series data and applications to biomedical signal processing and brain imaging. Marco A. R. Ferreira is an Associate Professor in the Department of Statistics at Virginia Tech, where he served from 2016 to 2020 as the Director of Graduate Programs. Mike West holds a Duke University distinguished chair as the Arts & Sciences Professor of Statistics & Decision Sciences in the Department of Statistical Science, where he led the development of statistics from 1990-2002.
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
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Taschenbuch |
| Seiten: | 452 |
| ISBN-13: | 9781032040042 |
| ISBN-10: | 1032040041 |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Ferreira, Marco A. R.
West, Mike Prado, Raquel |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 156 x 235 x 28 mm |
| Von/Mit: | Marco A. R. Ferreira (u. a.) |
| Erscheinungsdatum: | 25.09.2023 |
| Gewicht: | 0,71 kg |
Ähnliche Produkte
Aktuell nicht verfügbar
Lieferzeit 4-7 Werktage
Lieferzeit 2-3 Wochen
Lieferzeit 4-7 Werktage
Lieferzeit 4-7 Werktage
Lieferzeit 2-3 Wochen
Lieferzeit 1-2 Wochen
Lieferzeit 1-2 Wochen