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020 _a9783031516092
_9978-3-031-51609-2
024 7 _a10.1007/978-3-031-51609-2
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
100 1 _aHorváth, Lajos.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_974712
245 1 0 _aChange Point Analysis for Time Series
_h[electronic resource] /
_cby Lajos Horváth, Gregory Rice.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIII, 545 p. 36 illus., 30 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Statistics,
_x2197-568X
505 0 _aCumulative 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 _aThis 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.
650 0 _aMathematical statistics.
_967233
650 0 _aTime-series analysis.
_976645
650 0 _aBiometry.
_965981
650 0 _aStatistics .
_965982
650 1 4 _aMathematical Statistics.
_967233
650 2 4 _aTime Series Analysis.
_976646
650 2 4 _aBiostatistics.
_965985
650 2 4 _aStatistics in Business, Management, Economics, Finance, Insurance.
_969738
700 1 _aRice, Gregory.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_976647
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031516085
776 0 8 _iPrinted edition:
_z9783031516108
776 0 8 _iPrinted edition:
_z9783031516115
830 0 _aSpringer Series in Statistics,
_x2197-568X
_976648
856 4 0 _uhttps://doi.org/10.1007/978-3-031-51609-2
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c59774
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