Description
Taylor & Francis Analysis Of Time Series An Introduction With R 7Th Edition by Chris Chatfield
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 modelsA revised chapter on linear time series modelsA new section on multivariate volatility modelsA new section on regime switching modelsMany new worked examples, with R code integrated into the textThe 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. IntroductionBasic Descriptive TechniquesSome Linear Time Series ModelsFitting Time Series Models in the Time DomainForecastingStationary Processes in the Frequency DomainSpectral AnalysisBivariate ProcessesLinear SystemsState-Space Models and the Kalman FilterNon-Linear ModelsVolatility ModelsMultivariate Time Series ModellingSome More Advanced TopicsAppendix A Fourier, Laplace, and z-TransformsAppendix B Dirac Delta FunctionAppendix C Covariance and CorrelationAnswers to Exercises