Description
Book SynopsisExplaining the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two statistical packages - SAS and SPSS. It also features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation.
Trade Review"Robert Yaffee has performed an invaluable service to students of time series analysis by preparing an introduction to methods for analyzing time series data that includes examples drawn from the social sciences, and demonstrates how to program the procedures in SPSS and SAS. Introduction to Time Series Analysis and Forecasting will be a standard reference for years to come." --DAVID F. GREENBERG, New York University, New York
Table of ContentsPreface. Introduction and Overview. Extrapolative Models and Decomposition Models. Introduction to Box-Jenkins Time Series Analysis. The Basic ARIMA Model. Seasonal ARIMA Models. Estimation and Diagnosis. Metadiagnosis and Forecasting. Intervention Analysis. Transfer Function Models. Autoregressive Error Models. A Review of Model and Forecast Evaluation. M. McGee, Power Analysis and Sample Size Determination for Well-Known Time Series Models. Appendix A. Glossary. Index.
