An Introduction to Time Series Analysis and Forecasting: With Applications of SAS� and SPSS�

Yaffee, Robert Alan

ISBN 10: 0127678700 / ISBN 13: 9780127678702

Published by Academic Press, 2000

About this Item

Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Seller Inventory # Z1-K-021-02179

Bibliographic Details

Title: An Introduction to Time Series Analysis and ...

Publisher: Academic Press

Publication Date: 2000

Binding: Hardcover

Condition: Good

About this title

Synopsis:

Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation, along with a sample size analysis for common time series models to attain adequate statistical power. The careful linkage of the theoretical constructs with the practical considerations involved in utilizing the statistical packages makes it easy for the user to properly apply these techniques.

• Describes principal approaches to time series analysis and forecasting
• Presents examples from public opinion research, policy analysis, political science, economics, and sociology
• Math level pitched to general social science usage
• Glossary makes the material accessible for readers at all levels

From the Back Cover:

Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features methods of combining forecasts, model and forecast evaluation, along with a sample size analysis for common time series models. The careful linkage of the theoretical constructs with the practical considerations involved in utilizing the statistical package makes it easy for the user to properly apply these techniques.