Description

Book Synopsis
Explaining 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 Contents
Preface. 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.

An Introduction to Time Series Analysis and Forecasting

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    A Hardback by Monnie McGee, Monnie McGee

    15 in stock

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      Publisher: Elsevier Science
      Publication Date: Publication Date: 5/12/2000 12:00:00 AM
      ISBN13: 9780127678702, 978-0127678702
      ISBN10: 0127678700
      Also in:
      Social research and statistics

      Description

      Book Synopsis
      Explaining 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 Contents
      Preface. 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.

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