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Change Point Analysis for Time Series

BuchGebunden
545 Seiten
Englisch
Springererschienen am12.05.20242024
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.mehr
Verfügbare Formate
BuchGebunden
EUR139,09
E-BookPDF1 - PDF WatermarkE-Book
EUR128,39

Produkt

KlappentextOverall, "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.
Details
ISBN/GTIN978-3-031-51608-5
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2024
Erscheinungsdatum12.05.2024
Auflage2024
ReiheSpringer Series in Statistics
Seiten545 Seiten
SpracheEnglisch
Gewicht941 g
IllustrationenXIII, 545 p. 36 illus., 30 illus. in color.
Artikel-Nr.55692372

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Schlagworte

Autor

Lajos Horváth is a faculty member in the Department of Mathematics at the University of Utah. He has coauthored over 300 peer reviewed papers and 5 books in the areas of statistics and probability on the topics of empirical process theory, functional data analysis, and change point analysis. He became a fellow at the Institute of Mathematical Statistics in 1990. He has been acknowledged as an ISI highly cited researcher. In addition to his research, Lajos has played significant editorial roles in several top research journals, including Statistics & Probability Letters, Journal of Statistical Planning and Inference and Journal of Time Series Econometrics.
Gregory Rice is a faculty member in the Department of Statistics and Actuarial Science at the University of Waterloo. He received his undergraduate degree in mathematics from Oregon State University, and a PhD in mathematics from the University of Utah. He has coauthored over 40 papers in theareas of functional data and time series analysis. His work has been supported by the Natural Science and Engineering Research Council of Canada Discovery Accelerator program.
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Rice, Gregory