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About This Book
About The Authors
Chapter 1: Overview of Time Series
1.2 Analysis Methods and SAS/ETS Software
1.2.2 How SAS/ETS Procedures Interrelate
1.3 Simple Models: Regression
1.3.1 Linear Regression
1.3.2 Highly Regular Seasonality
1.3.3 Regression with Transformed Data
Chapter 2: Simple Models: Autoregression
2.1.1 Terminology and Notation
2.1.2 Statistical Background
2.2.1 PROC ARIMA for Forecasting
2.2.2 Backshift Notation B for Time Series
2.2.3 Yule-Walker Equations for Covariances
2.3 Fitting an AR Model in PROC REG
Chapter 3: The General ARIMA Model
3.1.1 Statistical Background
3.1.2 Terminology and Notation
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