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.
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
