Documentation Table of Contents

Part 1. Summary of Time Series Functions

1.2 Data Smoothing

Part 2. User's Guide to Time Series

2.2 Stationary Time Series Models

• Autoregressive Moving Average Models
• Stationarity
• Covariance and Correlation Functions
• Partial Correlation Functions
• Multivariate ARMA Models

2.3 Nonstationary and Seasonal Models

• ARIMA Process
• Seasonal ARIMA Process

2.4 Preparing Data for Modeling

• Plotting the Data
• Generating Time Series
• Transformation of Data

2.5 Estimation of Correlation Function and Model Identification

• Estimation of Covariance and Correlation Functions
• The Asymptotic Distribution of the Sample Correlation Function
• The Sample Partial Correlation Function
• Model Identification
• Order Selection for Multivariate Series

2.6 Parameter Estimation and Diagnostic Checking

• Parameter Estimation
• Diagnostic Checking

2.7 Forecasting

• Best Linear Predictor
• Large Sample Approximation to the Best Linear Predictor
• Updating the Forecast
• Forecasting for ARIMA and Seasonal Models
• Exponential Smoothing
• Forecasting for Multivariate Time Series

2.8 Spectral Analysis

• Power Spectral Density Function
• The Spectra of Linear Filters and of ARMA Models
• Estimation of the Spectrum
• Smoothing the Spectrum
• Spectrum for Multivariate Time Series

2.9 Examples of Analysis of Time Series