Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • 1
    UID:
    b3kat_BV049725106
    Format: 1 Online-Ressource (xiii, 545 Seiten) , Illustrationen
    ISBN: 9783031516092
    Series Statement: Springer series in statistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-51608-5
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-51610-8
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-51611-5
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Cham :Springer Nature Switzerland :
    UID:
    almahu_9949744368102882
    Format: XIII, 545 p. 36 illus., 30 illus. in color. , online resource.
    Edition: 1st ed. 2024.
    ISBN: 9783031516092
    Series Statement: Springer Series in Statistics,
    Content: 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.
    Note: 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.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783031516085
    Additional Edition: Printed edition: ISBN 9783031516108
    Additional Edition: Printed edition: ISBN 9783031516115
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Online Resource
    Online Resource
    Cham : Springer Nature Switzerland | Cham : Imprint: Springer
    UID:
    gbv_1888478446
    Format: 1 Online-Ressource(XIII, 545 p. 36 illus., 30 illus. in color.)
    Edition: 1st ed. 2024.
    ISBN: 9783031516092
    Series Statement: Springer Series in Statistics
    Content: 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.
    Content: 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.
    Additional Edition: ISBN 9783031516085
    Additional Edition: ISBN 9783031516108
    Additional Edition: ISBN 9783031516115
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031516085
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031516108
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031516115
    Additional Edition: Erscheint auch als Druck-Ausgabe Horváth, Lajos, 1956 - Change point analysis for time series Cham : Springer Nature, 2024 ISBN 9783031516085
    Additional Edition: ISBN 9783031516108
    Additional Edition: ISBN 9783031516115
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Did you mean 9783031511615?
Did you mean 9783031161155?
Did you mean 9783031156175?
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages