7th Edition

The Analysis of Time Series
An Introduction with R





ISBN 9781498795630
Published May 9, 2019 by Chapman and Hall/CRC
398 Pages 85 B/W Illustrations

USD $79.95

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Book 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. It also presents many examples and implementations of time series models and methods to reflect advances in the field.

Highlights of the seventh edition:

  • A new chapter on univariate volatility models
  • A revised chapter on linear time series models
  • A new section on multivariate volatility models
  • A new section on regime switching models
  • Many new worked examples, with R code integrated into the text

The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.

Table of Contents

Introduction

Basic Descriptive Techniques

Some Linear Time Series Models

Fitting Time Series Models in the Time Domain

Forecasting

Stationary Processes in the Frequency Domain

Spectral Analysis

Bivariate Processes

Linear Systems

State-Space Models and the Kalman Filter

Non-Linear Models

Volatility Models

Multivariate Time Series Modelling

Some More Advanced Topics

Appendix A Fourier, Laplace, and z-Transforms

Appendix B Dirac Delta Function

Appendix C Covariance and Correlation

Answers to Exercises

 

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Author(s)

Biography

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.

Reviews

"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