The Analysis of Time Series
An Introduction with R
7th Edition
Published on 25. April 2019
414 pages
978-1-4987-9564-7 (ISBN)
Description
This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.
Reviews / Votes
"Chris Chatfield has already written some popular books in statistics. Haipeng Xing is also a renowned researcher in statistics with more than 8000 citation. Efforts have been made by both authors to publish reliable data and information relating to different applications... The best part of the book is that some exercises are explained explicitly with sufficient hints. The authors also review several books on time series by other researchers from 1971 to 2010...Overall, this book is a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis in a wide range of topics. The book is intended for masters and undergraduate students in mathematics, probability, economics, statistics, astrophysics, biomedical engineering, and neuroscience. However, students who are early in a relevant PhD programme should also read this book to gain fundamental background knowledge."- Chitaranjan Mahapatra, ISCB News, July 2020
"One would never fail to notice the accessibility and the patience with which the authors introduce each of the topics in this classical textbook. The new edition successfully continues the style of the past editions, to be the one of the most accessible textbook on time series analysis. It introduces the topics with intuitions, followed with the most necessary technical details. I am particularly pleased that the R-code and data sets accompanying all the graphical analysis throughout the book, appear right where the definitions are introduced, satisfying the immediate curiosity of the readers. Together with the homework, they provide a nice platform to engage in description, explanation, prediction and control using time series data. Many data sets are updated or newly incorporated, relative to the previous version. A must-read for anyone interested in an introduction to time series."
- Feng Yao, West Virginia University
More details
Series
Edition
7th edition
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Illustrations
85 Line drawings, black and white; 85 Illustrations, black and white
File size
3,60 MB
ISBN-13
978-1-4987-9564-7 (9781498795647)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
05/2019
7th Edition
Chapman & Hall/CRC
€113.10
Shipment within 15-20 days
Book
05/2019
7th Edition
CRC Press
€254.70
Shipment within 10-20 days
Persons
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 Honorary Fellow of the International Institute of Forecasters.
Haipeng Xing is an associate professor in Applied Mathematics and Statistics at the State University of New York, Stony Brook, USA, the author of two books and numerous research papers. His research interests include quantitative finance and risk management, econometrics, applied stochastic control, and sequential statistical methodology.
Haipeng Xing is an associate professor in Applied Mathematics and Statistics at the State University of New York, Stony Brook, USA, the author of two books and numerous research papers. His research interests include quantitative finance and risk management, econometrics, applied stochastic control, and sequential statistical methodology.
Content
1. Introduction 2. Basic Descriptive Techniques 3. Some Linear Time Series Models 4. Fitting Time Series Models in the Time Domain 5. Forecasting 6. Stationary Processes in the Frequency Domain 7. Spectral Analysis 8. Bivariate Processes 9. Linear Systems 10. State-Space Models and the Kalman Filter 11. Non-Linear Models 12. Volatility Models 13. Multivariate Time Series Modelling 14. Some More Advanced Topics Appendix A Fourier, Laplace, and z-Transforms. Appendix B Dirac Delta Function. Appendix C Covariance and Correlation. Answers to Exercises.
