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.
Autorentext
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.
Inhalt
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