Change point analysis for time series:
This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go be...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2024]
|
| Ausgabe: | 1st ed. 2024 |
| Schriftenreihe: | Springer Series in Statistics
|
| Schlagworte: | |
| Zusammenfassung: | This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go beyond the traditional change point methods for univariate and multivariate series. It also explores techniques for handling heteroscedastic series, high-dimensional series, and functional data. While the primary emphasis is on retrospective change point analysis, the book also presents sequential "on-line" methods for detecting change points in real-time scenarios. Each chapter in the book includes multiple data examples that illustrate the practical application of the developed results. These examples cover diverse fields such as economics, finance, environmental studies, and health data analysis. To reinforce the understanding of the material, each chapter concludes with several exercises.Additionally, the book provides a discussion of background literature, allowing readers to explore further resources for in-depth knowledge on specific topics. Overall, "Change Point Analysis for Time Series" offers a broad and informative overview of modern methods in change point analysis, making it a valuable resource for researchers, practitioners, and students interested in analyzing and modeling time series data |
| Beschreibung: | xiii, 545 Seiten Illustrationen 235 mm |
| ISBN: | 9783031516085 |
Internformat
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| 520 | |a This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go beyond the traditional change point methods for univariate and multivariate series. It also explores techniques for handling heteroscedastic series, high-dimensional series, and functional data. While the primary emphasis is on retrospective change point analysis, the book also presents sequential "on-line" methods for detecting change points in real-time scenarios. Each chapter in the book includes multiple data examples that illustrate the practical application of the developed results. These examples cover diverse fields such as economics, finance, environmental studies, and health data analysis. To reinforce the understanding of the material, each chapter concludes with several exercises.Additionally, the book provides a discussion of background literature, allowing readers to explore further resources for in-depth knowledge on specific topics. Overall, "Change Point Analysis for Time Series" offers a broad and informative overview of modern methods in change point analysis, making it a valuable resource for researchers, practitioners, and students interested in analyzing and modeling time series data | ||
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Datensatz im Suchindex
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| id | DE-604.BV049656022 |
| illustrated | Illustrated |
| index_date | 2024-07-03T23:40:44Z |
| indexdate | 2024-08-24T01:04:06Z |
| institution | BVB |
| isbn | 9783031516085 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034999371 |
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| physical | xiii, 545 Seiten Illustrationen 235 mm |
| publishDate | 2024 |
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| publisher | Springer |
| record_format | marc |
| series2 | Springer Series in Statistics |
| spelling | Horváth, Lajos 1956- Verfasser (DE-588)170402908 aut Change point analysis for time series Lajos Horváth, Gregory Rice Cham Springer [2024] xiii, 545 Seiten Illustrationen 235 mm txt rdacontent n rdamedia nc rdacarrier Springer Series in Statistics This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go beyond the traditional change point methods for univariate and multivariate series. It also explores techniques for handling heteroscedastic series, high-dimensional series, and functional data. While the primary emphasis is on retrospective change point analysis, the book also presents sequential "on-line" methods for detecting change points in real-time scenarios. Each chapter in the book includes multiple data examples that illustrate the practical application of the developed results. These examples cover diverse fields such as economics, finance, environmental studies, and health data analysis. To reinforce the understanding of the material, each chapter concludes with several exercises.Additionally, the book provides a discussion of background literature, allowing readers to explore further resources for in-depth knowledge on specific topics. Overall, "Change Point Analysis for Time Series" offers a broad and informative overview of modern methods in change point analysis, making it a valuable resource for researchers, practitioners, and students interested in analyzing and modeling time series data bicssc bisacsh Time-series analysis Biometry Statistics Mathematical statistics Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik Rice, Greg Verfasser (DE-588)1332362508 aut Erscheint auch als Online-Ausgabe 978-3-031-51609-2 |
| spellingShingle | Horváth, Lajos 1956- Rice, Greg Change point analysis for time series bicssc bisacsh Time-series analysis Biometry Statistics Mathematical statistics |
| title | Change point analysis for time series |
| title_auth | Change point analysis for time series |
| title_exact_search | Change point analysis for time series |
| title_exact_search_txtP | Change Point Analysis for Time Series |
| title_full | Change point analysis for time series Lajos Horváth, Gregory Rice |
| title_fullStr | Change point analysis for time series Lajos Horváth, Gregory Rice |
| title_full_unstemmed | Change point analysis for time series Lajos Horváth, Gregory Rice |
| title_short | Change point analysis for time series |
| title_sort | change point analysis for time series |
| topic | bicssc bisacsh Time-series analysis Biometry Statistics Mathematical statistics |
| topic_facet | bicssc bisacsh Time-series analysis Biometry Statistics Mathematical statistics |
| work_keys_str_mv | AT horvathlajos changepointanalysisfortimeseries AT ricegreg changepointanalysisfortimeseries |