Time Series : A Data Analysis Approach Using R (Hardcover)

1. Time Series Elements Introduction Time Series Data Time Series Models Problems 2. Correlation and Stationary Time Series Measuring Dependence Stationarity Estimation of Correlation Problems 3. Time Series Regression and EDA Ordinary Least Squares for Time Series Exploratory Data Analysis Smoothing Time Series Problems 4. ARMA Models Autoregressive Moving Average Models Correlation Functions Estimation Forecasting Problems 5. ARIMA Models Integrated Models Building ARIMA Models Seasonal ARIMA Models Regression with Autocorrelated Errors * Problems 6. Spectral Analysis and Filtering Periodicity and Cyclical Behavior The Spectral Density Linear Filters * Problems 7. Spectral Estimation Periodogram and Discrete Fourier Transform Nonparametric Spectral Estimation Parametric Spectral Estimation Coherence and Cross-Spectra * Problems 8. Additional Topics * GARCH Models Unit Root Testing Long Memory and Fractional Differencing State Space Models Cross-Correlation Analysis and Prewhitening Bootstrapping Autoregressive Models Threshold Autoregressive Models Problems Appendix A R Supplement Installing R Packages and ASTSA Getting Help Basics Regression and Time Series Primer Graphics Appendix B Probability and Statistics Primer Distributions and Densities Expectation, Mean and Variance Covariance and Correlation Joint and Conditional Distributions Appendix C Complex Number Primer Complex Numbers Modulus and Argument The Complex Exponential Function Other Useful Properties Some Trigonometric Identities Appendix D Additional Time Domain Theory MLE for an AR() Causality and Invertibility ARCH Model Theory Hints for Selected Exercises