Time Series Analysis and Forecasting by Example
Language: English
Published by John Wiley & Sons Inc, 2011
- First Edition
- Hardcover
- New

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AbeBooks seller since February 27, 2001
Condition: New
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Add to basketItem description from seller
Times Series Analysis and Forecasting presents seemingly difficult techniques and methodologies in an insightful and application-based way. Through a hands-on and user-friendly approach, this text includes exercises, graphical techniques, examples, excel spreadsheets, and software applications on time series analysis. Series: Wiley Series in Probability and Statistics. Num Pages: 400 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 236 x 163 x 25. Weight in Grams: 712. . 2011. 1st Edition. Hardcover. . . . .
Seller Inventory # V9780470540640
- Title
- Time Series Analysis and Forecasting by Example
- Author
- S?ren Bisgaard
- Publisher
- John Wiley & Sons Inc
- Publication year
- 2011
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0470540648
- ISBN 13
- 9780470540640
- Edition
- 1st Edition
An intuition-based approach enables you to master time series analysis with ease
Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications.
The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including:
- Graphical tools in time series analysis
- Procedures for developing stationary, non-stationary, and seasonal models
- How to choose the best time series model
- Constant term and cancellation of terms in ARIMA models
- Forecasting using transfer function-noise models
The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets.
With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.
"Synopsis" may belong to another edition of this title.
About the Author
Murat Kulahci, PhD, is Associate Professor of Statistics in the Department of Informatics and Mathematical Modeling at the Technical University of Denmark. He has authored or coauthored over forty journal articles in the areas of time series analysis, design of experiments, and statistical process control and monitoring. Dr. Kulahci is coauthor of Introduction to Time Series Analysis and Forecasting (Wiley).
"About the title" may belong to another edition of this title.
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