The Analysis of Time Series
Language: English
Published by Taylor and Francis Ltd, GB, 2026
Series: Book 121 of 126 - Chapman & Hall/CRC Texts in Statistical Science
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
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Add to basketItem description from seller
Seller Inventory # LU-9781041026334
- Title
- The Analysis of Time Series
- Author
- Haipeng Xing, Chris Chatfield
- Publisher
- Taylor and Francis Ltd, GB
- Publication year
- 2026
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1041026331
- ISBN 13
- 9781041026334
- Item weight
- 770 grams
- Series
- Book 121 of 126: Chapman & Hall/CRC Texts in Statistical Science
The field of time series analysis has undergone a remarkable transformation since the publication of the seventh edition of this book. While classical statistical models such as autoregressive integrated moving average (ARIMA), state-space models, and spectral methods remain essential, the rise of artificial intelligence (AI) has introduced groundbreaking approaches to modelling, forecasting, and generating time-dependent data. This eighth edition of The Analysis of Time Series: An Introduction with R reflects these advancements with the addition of two new chapters: Predictive AI for Time Series and Generative AI for Time Series. These chapters bridge the gap between traditional time series methods and cutting-edge AI techniques, offering readers a comprehensive and integrated perspective on the field.
Features
- Comprehensive coverage of classical time series models including ARIMA, state-space models, and spectral methods
- Two new chapters on predictive and generative AI, introducing cutting-edge methods like transformers, variational autoencoders, and diffusion models
- Practical examples and illustrations using R, demonstrating the application of both classical and AI-based approaches to real-world time series data
- Emphasis on the integration of classical statistical rigor with the flexibility and scalability of AI methods
- Clear explanations and intuitive insights, making advanced concepts accessible to a broad audience
- Updated content reflecting the latest developments in time series analysis, with a focus on modern, high-dimensional, and nonlinear data challenges
The Analysis of Time Series: An Introduction with R, Eighth Edition is designed for students, researchers, and practitioners in statistics, as well as in finance, economics, climate science, health, and engineering. It serves as both a foundational text for those new to time series analysis and a valuable resource for experienced analysts seeking to engage with the rapidly evolving landscape of predictive and generative AI. With its balance of theory, practical implementation, and real-world examples, the book is ideal for use in academic courses, professional training, and self-study.
"Synopsis" may belong to another edition of this title.
About the Author
Haipeng Xing is a professor in applied mathematics and statistics at the State University of New York, Stony Brook, USA, the author of three books and numerous research papers. His research interests include quantitative finance and risk management, econometrics, applied stochastic control, and sequential statistical methodology.
Chris Chatfield is a retired reader in statistics at the University of Bath, UK, the author of five books and numerous research papers, and an elected senior fellow of the International Institute of Forecasters.
"About the title" may belong to another edition of this title.
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