A Course in Time Series Analysis
Language: English
Published by John Wiley and Sons Inc, US, 2000
- Hardcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
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New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time seriesShared balance between theory and applicationExercise series setsMany real data examplesConsistent style and clear, common notation in all contributions60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.…
Seller Inventory # LU-9780471361640
- Title
- A Course in Time Series Analysis
- Author
- Daniel Peña, George C. Tiao, Ruey S. Tsay
- Publisher
- John Wiley and Sons Inc, US
- Publication year
- 2000
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 047136164X
- ISBN 13
- 9780471361640
- Item weight
- 824 grams
New statistical methods and future directions of research in time series
A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include:
- Contributions from eleven of the worldâ??s leading figures in time series
- Shared balance between theory and application
- Exercise series sets
- Many real data examples
- Consistent style and clear, common notation in all contributions
- 60 helpful graphs and tables
Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis.
An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.
"Synopsis" may belong to another edition of this title.
About the Author
DANIEL PEÑA, PhD, is Professor of Statistics, Universidad Carlos III de Madrid.
GEORGE C. TIAO, PhD, is W. Allen Wallis Professor of Statistics and Econometrics, Graduate School of Business, University of Chicago.
RUEY S. TSAY, PhD, is H. G. B. Alexander Professor of Statistics and Econometrics, Graduate School of Business, University of Chicago.
"About the title" may belong to another edition of this title.
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