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...
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| Main Authors: | , |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edition: | 1st ed. 2024. |
| Series: | Springer Series in Statistics,
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-031-51609-2 |
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| 100 | 1 | |a Horváth, Lajos. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Change Point Analysis for Time Series |h [electronic resource] / |c by Lajos Horváth, Gregory Rice. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XIII, 545 p. 36 illus.). |b 30 illus. in color. | ||
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| 490 | 1 | |a Springer Series in Statistics, |x 2197-568X | |
| 505 | 0 | |a Cumulative Sum Processes -- Change Point Analysis of the Mean -- Variance Estimation, Change Points in Variance, and Heteroscedasticity -- Regression Models -- Parameter Changes in Time Series Models -- Sequential Monitoring -- High-dimensional and Panel Data -- Functional Data. | |
| 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Time-series analysis. | |
| 650 | 0 | |a Biometry. | |
| 650 | 0 | |a Statistics . | |
| 650 | 1 | 4 | |a Mathematical Statistics. |
| 650 | 2 | 4 | |a Time Series Analysis. |
| 650 | 2 | 4 | |a Biostatistics. |
| 650 | 2 | 4 | |a Statistics in Business, Management, Economics, Finance, Insurance. |
| 700 | 1 | |a Rice, Gregory. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
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