Time series analysis and its applications with R examples

Preface to the Fourth Edition Preface to the Third Edition 1 Characteristics of Time Series 1£®1 The Nature of Time Series Data 1£®2 Time Series Statistical Models 1£®3 Measures of Dependence 1£®4 Stationary Time Series 1£®5 Estimation of Correlation 1£®6 Vector-Valued and Multidimensional Series Problems 2 Time Series Regression and Exploratory Data Analysis 2£®1 Classical Regression in the Time Series Context 2£®2 Exploratory Data Analysis 2£®3 Smoothing in the Time Series Context Problems 3 ARIMA Models 3£®1 Autoregressive Moving Average Models 3£®2 Difference Equations 3£®3 Autocorrelation and Partial Autocorrelation 3£®4 Forecasting 3£®5 Estimation 3£®6 Integrated Models for Nonstationary Data 3£®7 Building ARIMA Models 3£®8 Regression with Autocorrelated Errors 3£®9 Multiplicative Seasonal ARIMA Models Problems 4 Spectral Analysis and Filtering 4£®1 Cyclical Behavior and Periodicity 4£®2 The Spectral Density 4£®3 Periodogram and Discrete Fourier Transform 4£®4 Nonparametric Spectral Estimation 4£®5 Parametric Spectral Estimation 4£®6 Multiple Series and Cross-Spectra 4£®7 Linear Filters 4£®8 Lagged Regression Models 4£®9 Signal Extraction and Optimum Filtering 4£®10 Spectral Analysis of Multidimensional Series Problems 5 Additional Time Domain Topics 5£®1 Long Memory ARMA and Fractional Differencing 5£®2 Unit Root Testing 5£®3 GARCH Models 5£®4 Threshold Models 5£®5 Lagged Regression and Transfer Function Modeling 5£®6 Multivariate ARMAX Models Problems 6 State Space Models 6£®1 Linear Gaussian Model 6£®2 Filtering£¬ Smoothing£¬and Forecasting 6£®3 Maximum Likelihood Estimation 6£®4 Missing Data Modifications 6£®5 Structural Models£º Signal Extraction and Forecasting 6£®6 State-Space Models with Correlated Errors 6£®6£®1 ARMAX Models 6£®6£®2 Multivariate Regression with Autocorrelated Errors 6£®7 Bootstrapping State Space Models 6£®8 Smoothing Splines and the Kalman Smoother 6£®9 Hidden Markov Models and Switching Aut oregression 6£®10 Dynamic Linear Models with Switching 6£®1£®1 Stochastic Volatility 6£®1£®2 Bayesian Analysis of State Space Models Problems 7 Statistical Methods in the Frequency Domain 7£®1 Introduction 7£®2 Spectral Matrices and Likelihood Functions 7£®3 Regression for Joindy Stationary Series 7£®4 Regression with Deterministic Inputs 7£®5 Random Coefficient Regression ¡­¡­ Appendix A Large Sample Theory Appendix B Time Domain Theory Appendix C SpectraIDomain Theory Appendix R R Supplement References Index